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Unitree G1 and H2 Robots Stun With Autonomous Martial Arts Show

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Atlas Airborne | Boston Dynamics & @rai-inst

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Chine : fin des Jeux mondiaux de robots humanoïdes • FRANCE 24

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Les 30 nouveaux robots de 2025 qui sont d'un autre niveau !

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En Chine, les robots ont droit à leurs premiers JO (mais les humains n’ont pas à s’inquiéter)

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La Chine dévoile les robots les plus incroyables au salon FAIR PLUS EXPO 2025

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E-Doggy aide les agriculteurs à gérer leurs poules

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E-Doggy aide les agriculteurs à gérer leurs poules

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Comment le robot E-Doggy aide les agriculteurs à gérer leurs poules sans peur

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Arm you glad to see me, Atlas? | Boston Dynamics

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Walk, Run, Crawl, RL Fun | Boston Dynamics | Atlas

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Des robots courent le semi-marathon de Pékin

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Des robots courent le semi-marathon de Pékin

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Chine : des robots courent le semi-marathon de Pékin

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Boston Dynamics releases video of Atlas robot that now needs zero help from humans to perform tasks

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Introducing Unitree Go2 - Quadruped Robot of Embodied AI from $1600

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Fast Line Follower Robot Race 🔥 #robotic #robot #linefollower #automobile #competition #technology

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Unitree G1: A New Era of Humanoid Robots

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Robots ou humains ? Vous n'arriverez plus à faire la différence. Je vous dit tout !

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Le robot humanoïde de Boston Dynamics, Atlas, laisse sa place à un nouveau modèle électrique

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Beyond modern: a review of the CES-2024 show in Las Vegas | Robots and cars with ai | Pro Robots

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L'histoire de l'intelligence artificielle en 7 dates.

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L'histoire de l'intelligence artificielle en 7 dates.

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China has Released its Most Advanced Robots that Can Do Anything

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WRC 2023 - La plus grande exposition de robot en Chine

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WRC 2023 - La plus grande exposition de robot en Chine

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WRC 2023 - China's largest robot exhibition | Robots and technologies at the exhibition in China

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MOULLA - DroneBrella - Self Flying Umbrella - Augmented Magic

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Autofuel Introduced It's Fully Automated Robotic Refueling System

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ICRA 2023: The best robots that will change the world! | Robots of the future | Pro Robots

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Daisy, le robot qui désosse nos vieux iPhone

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Daisy, le robot qui désosse nos vieux iPhone

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Daisy, le robot d’Apple qui désosse nos vieux iPhone

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The Next Generation Of Digit - Enabling Humans To Be More Human

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Apollo, le robot à tout faire de la NASA

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Apollo, le robot à tout faire de la NASA

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自在肢 | JIZAI ARMS: SOCIAL DIGITAL CYBORGS

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7 Farming ROBOTS to change agriculture | WATCH NOW ▶ 2 !

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Le site du magazine.

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Ce rachat fait suite à un contrat portant sur plus de 2000 robots conclu avec DHL, la plus grande entreprise de logistique au monde. Locus et Waypoint, au cœur des...

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Chaîne Youtube

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robot bigdog atlas "legged locomotion" "boston dynamics" "spot robot" "dynamic robots" spot stretch pick

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Boston Dynamics' mission is to imagine and create exceptional robots that enrich people's lives. For more information about Boston Dynamics and our robots, visit us at https://www.bostondynamics.com.

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robots robotics cassie technolgoy tech software hardware "artificial intelligence" ai "machine learning" perception engineering

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We're here to build robots for good. Robots that help businesses and people thrive. #MadeForWork

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C'est quoi l'intelligence artificielle ?

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C'est quoi l'intelligence artificielle ?

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C'est quoi l'intelligence artificielle ? - 1 jour, 1 question

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L'ALGORITHME DANS LA PEAU

Un dossier préparé par Melvin Martineau et Julie Desriac
Avec le parrainage de Olivier Schouteeten, généreux tipeur

Faites défiler la page de haut en bas
pour parcourir tout notre dossier. Bonne visite !

Dans la tête d'une Intelligence Artificielle

De la naissance à l'âge adulte

Passez le curseur sur les fusées et les épingles rouges pour accéder aux contenus

Lorène Allano, Olivier Bichler, Quoc Cuong Pham et Patrick Sayd, chercheurs au CEA

Philippe Esling et Jérôme Nika, chercheurs à l'IRCAM

Alexei Grinbaum, philosophe des sciences à la CERNA et physicien au CEA

Quel impact a l'IA sur notre société ?

L'IA peut-elle dépasser l'humain ?

Quels sont les métiers menacés par l'IA ?

Comment créer de la confiance entre les IA et les humains ?

Personne électronique : un nouveau statut juridique pour les IA ?

Donnez votre avis et découvrez celui de la communauté

Qui a dit : "L'intelligence artificielle se définit comme le contraire de la bêtise naturelle" ?

Retrouvez toutes nos vidéos sur la chaîne Youtube de l'Esprit Sorcier Suivez-nous sur Facebook et Twitter Soutenez-nous sur Tipeee !

Le temps des algorithmes, Serge Abiteboul & Gilles Dowek, éditions Le Pommier, 2017

Apprentissage artificiel, Antoine Cornuéjols & Laurent Miclet, éditions Eyrolles, 2002

Histoire et évolution de l'Intelligence Artificielle, Marco Casella, 2014

Remerciements

Lorène Allano - Ingénieure-chercheuse en machine learning au CEA-List
Olivier Bichler - Ingénieur-chercheur en deep learning au CEA-List
Julien Chiaroni - Adjoint au Directeur du CEA-List, en charge de la Stratégie et des Programmes
Bertrand Delezoide - Chercheur au CEA-List
Jérôme Gauthier - Ingénieur-chercheur en IA au CEA-List
Alexei Grinbaum - Philosophe des sciences à la CERNA et physicien au CEA
Anthony Larue - Chercheur au CEA-List
Elisabeth Lefèvre-Rémy - Responsable communication au CEA-List
Quoc Cuong Pham - Chercheur en vision artificielle au CEA-List
Patrick Sayd - Chef du laboratoire vision et ingénierie des contenus au CEA-List
Oriane Joubé - Chargée de communication web en alternance au CEA
Céline Lipari - Responsable éditoriale du site internet
Frédéric Fürst - Chercheur à l'Université de Picardie
Bertrand Braunschweig - Directeur du centre Inria de saclay
Eleonore Schiltz - Membre du laboratoire Neuroscience Cognitive - ENS
Philippe Esling - Chercheur en IA appliquée à la musique à l'IRCAM
Jérôme Nika - Chercheur en interaction musicale Humain/Machine à l'IRCAM
Rémi Fox - Saxophoniste, improvisateur
Marc-Henri Lamande - Artiste

Merci aux équipes de l'IRCAM pour leur accueil
Merci aux éditions Le Pommier
Merci à l'ensemble des équipes du CEA
Merci à Gabriel Fricout et aux équipes d'ArcelorMittal Maizières Process, Global Research and Development

Crédits images

© L'Esprit Sorcier - Avril 2018

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Intelligence Artificielle - L'Esprit Sorcier - Dossier #33

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Fred Courant et l'équipe de C'est pas Sorcier 2.0 décryptent le fonctionnement et les applications de l'IA. Après ça, vous aurez l'algorithme dans la peau !

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Légendaire CES-2023 à Las Vegas // Voiture qui change de couleur et technologies futures

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Winky, le premier robot éducatif Made in France

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Média de décryptage, Futura vous emmène à la rencontre des découvertes et innovations qui changent le monde. Autour de 5 rubriques (Sciences, Santé, Tech, Maison et Planète), nos journalistes vous proposent un contenu exclusif : actualités, vidéos, dossiers, photos...

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Futuris - les dernières actus et infos | Euronews

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Tour d’horizon des projets de recherche majeurs dans les sciences et les technologies en Europe.

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Sci-tech - les dernières actus et infos | Euronews

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Recevez les dernières informations scientifiques et technologiques par le biais d’un regard en profondeur sur les développements scientifiques et hi-tech en Europe et dans le monde. Disponibles en vidéo à la demande.

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Chaîne Youtube

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robotique robots robot ia "intelligence artificielle" drones "nouvelles technologies" "high tech" actualités

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Bienvenue sur la chaîne PRO Robots ! Ici, nous partageons les futures technologies de pointe du monde des robots, des drones, de l'Intelligence Artificielle et de la réalité virtuelle, ainsi que des actualités, des critiques, les plus beaux accomplissements et des découvertes. Que peuvent faire les robots aujourd'hui et qu'apprendront-ils à l'avenir ?

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Chaine Youtube

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Fort de 14 années d'expérience dans la robotique, Génération Robots est un distributeur de robots et de composants robotiques et électroniques. Ce qui nous différencie ? Nous possédons notre propre bureau d'études en robotique, capable de concevoir des solutions robotiques avancées pour des secteurs variés (nucléaire, aéronautique, etc).

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L’intelligence artificielle: Qu’est-ce que c’est ?

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L’intelligence artificielle: Qu’est-ce que c’est ?

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L’intelligence artificielle: Qu’est-ce que c’est ?

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24:46 / 56:21

L’intelligence artificielle n’existe pas

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L’intelligence artificielle n’existe pas, par Luc Julia

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Comprendre l’IA : le machine learning  I Applied Intelligence

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Et si l’IA construisait nos maisons ?

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Et si l’IA construisait nos maisons ? | Twist | ARTE

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L'arrivée de l'intelligence artificielle ne se compare pas facilement avec des percées techniques antérieures car, à la différence d'inventions comme l'ordinateur, le moteur à explosion, le microscope ou l'imprimerie, elle ne fait rien de particulier en elle-même sinon que d'augmenter la portée de pratiquement toutes les percées techniques précédentes.

Par exemple, si le télescope a permis de sonder les profondeurs de l'espace, on a vite été submergés par les myriades de corps célestes dont au final on ne peut pas humainement suivre ni l'évolution ni les interactions. Avec une I.A. on le peut.

Ce genre de situation peut-être trouvé dans quasiment tous les domaines où il est question de grands nombres. Biologie, sciences humaines, physique, chimie, politique, de l'infiniment petit à l'infiniment grand, il nous devient possible de trouver et de créer des relations qui sont au delà des capacités humaines, soit en termes de temps de réalisation, de capacité d'observation, de mémorisation ou simplement de persistance d'attention.

Voici quelques applications récentes de l'I.A., pour nous faire rêver ou nous inquiéter.

Poised - Votre coach personnel pour améliorer votre expression orale et votre présentation. Un accélérateur d'entrainement.

ProfessorBob - À partir de vos manuels de cours ou de différentes sources non-structurées, génère des milliers d'exercices et activités. Une nouvelle ère s'annonce en pédagogie.

Reading Progress - I.A. dédiée à l'apprentissage de la lecture. Formidable et gratuit

Cleanup Pictures - Retirez n'importe quel objet, défaut, personne, texte d'une image en quelques secondes.

Craiyon - Génère des images à partir de mots, de concepts, d'idées. Résultats primitifs mais intéressants.

Designs.AI - Un esthétisme particulier ? Le voici adapté à vos besoins.

Dall-e-2 - Par Open A.I., génère des images à partir de mots, de concepts, d'idées. Résultats plus sophistiqués mais modérés.

Deep Art Effects - Transformer n'importe quelle photo ou image dans un style particulier. De l'appropriation culturelle systématisée, Impressionnant.

Jasper Art - Crée des images, mais aussi des textes, des titres et s'inspire de ce qui se trouve "tendance" dans Internet. Fou !

Lensa AI - Cette app transforme vos photos personnelles comme vous les voulez.

Magic Eraser - Retire ce que vous voulez d'une image en rétablissant l'arrière plan. Création d'images à partir d'idées.

Midjourney AI - Un générateur d'art plutôt troublant.

Mokker - Des photos de vos produits dans différents environnements générés, avec l'éclairage et les ombrages.

Pebblely - Dites l'environnement que vous désirez et votre produit sera mis en valeur. Comme Mokker

Stockimg.AI - Génération d'images, d'affiches, de logo, de tapisserie, de couvertures de livres, d'affiches à partir d'une amorce.

Dictation.io - Votre parole ou dictée retranscrite en 130 langues et accents, en direct et en ligne. Par Google

Krisp - Débarrasse vos communications de tout ce qui n'est pas votre conversation, en direct. Impressionnant.

Midomi - Fredonnez une chanson et Midomi retrouvera de quelle chanson il s'agit. Un service supporté par l'I.A. de SoudHound

Murf.AI - Récite vos textes de manière professionnelle et vivante.

Prime Voice AI - Copie votre voix, vos intonations, votre débit, votre style et lui fait dire ce que vous voulez. En anglais seulement , pour l'instant. Par EleverLabs. Troublant.

SoudHound - Assure l'interprétation des commandes par la voix dans toutes sortes d'industrie et d'applications.

AIVA - De la musique composée par une I.A. selon le style choisi, général ou spécifique. Comme pour les oeuvres d'art graphique, mais ici pour les oeuvres musicales.

Flow Machines - Première incursion dans la composition musicale par I.A. - Projet de Sony Musique. App

JukeBox - Par Open AI - Projet développé par Open AI. Le code source est disponible sur GitHub

Mubert - Générer de la musique de toutes les façons, même à partir de texte ! De quoi faire déborder votre coupe musicale.

Vocal Remover - L'algorithme retire la voix de la trame musicale. Idéal pour produire des trames de karaoke.

Texte

Chat GPT - Posez votre question, l'I.A. y répondra avec toute la puissance de Open AI. Impressionnant.

Copy AI - Écrit des textes optimisés. Utile pour ceux en panne d'imagination.

Excel Formula Bot - Transforme vos instructions textuelles en formules Excel et Google Sheets. "Sommation des colonnes A et B quand la colonne D est avant le 1er janvier 2023."

Friday - Outil de rédaction de contenu, en tout genre.

Giant Language model Test Room - Un outil IBM Watson qui se sert de la même logique probabiliste pour savoir si un texte est généré par une I.A. que celle qui a servi à le générer.

GPT-2 Output Detector Demo - Un outil pour vérifier si un texte a été composé par une I.A. Une I.A. est trop parfaite !

HyperWrite - Assistant à la rédaction pour les usagers de Chrome.

Jasper Art - Crée des textes, des titres mais aussi des images et s'inspire de ce qui se trouve "tendance" dans Internet. Fou !

Lia 27 - Une I.A. conversationnelle émotionnellement accommodante mais finalement stupide.

Longshot - Fact GPT - Assistant de rédaction. Pensez à Chat GPT, mais avec les sources et les citations et un vérificateur de plagiat.

PepperType - Écrit des textes optimisés pour la vente.

Perplexity - Un concurrent de Chat GPT, plus concis mais qui détaille ses sources.

Rytr - Assistant à la rédaction de courriels et autres textes.

Scalenut - La rédaction SEO au niveau supérieur, à partir des données du domaine que vous visez. Ouch !

Shortly - Votre assistant rédacteur. En panne d'inspiration ? Ça ne paraîtra presque pas.

Sparrow - La réponse de Google à ChatGPT... qui se fait toujours attendre

Talk to books - Posez une question, l'I.A. trouvera une réponse dans des millions de livres. Différent.

Tome - Raconte des histoires à partir d'une amorce et peut l'agrémenter de visuels ou de vidéos tout aussi artificiels. De quoi rendre perplexe bien des créateurs.

WriteSonic - Écrit à propos de n'importe quoi, pour vous.

Détecteurs de textes rédigés par une I.A. - Thot Cursus

Otter - Retransciption de réunion, de conversation...

Supernormal - Retranscription de réunion en ligne - Un peu invasif, requiert notre calendrier.

Whisper - Retranscrit toute parole en texte (vidéo, balado, réunion, radio...) - Code ouvert. Autre service de Open AI

Recherche

AlphaFold - Une réalisation de DeepMind qui montre bien le potentiel de l'I.A. pour résoudre des problèmes complexes. Rien pour jouer avec, mais une réalisation remarquable en recherche biologique : prédire la forme des protéines en 3D et leur comportement avec un haut degré de justesse.

Dactyl - Par Open AI - Entrainer une main artificielle à devenir aussi habile qu'une main humaine. Elle pourra taper à la machine, jouer du piano, réussir le cube Rubik d'une main... etc.

Wordtune Read - Pas le temps de tout lire, cette I.A lit pour vous et vous résume le tout. Document soumis et résumé en quelques secondes.

Traduction

DeepL - Actuellement la référence, mais la concurrence se rapproche

Google traduction - Ambitieux mais encore boiteux, plus de 100 langues

Assembly AI - Transcription et analyse de documents audio et vidéo. Si vous avez 10 ans de contenu audio ou vidéo à transcrire, cette application est absolument nécessaire.

Make-A-Video - Comme Dall-e, mais pour le vidéo. Un projet Meta.

Steve AI - Création de vidéos et d'animations à partir de sources que vous choisissez

Synthesia - Vidéos à partir de vos textes. Des dizaines d'avatars dont les expressions seront réalistes liront vos textes comme des vraies personnes, en plusieurs langues.

Topaz AI - De la retouche vidéo, restauration, amélioration de l'image

Wisecut - Remontage vidéo assisté par une I.A. Son et image...

Hypertrucages vidéos
Illustration : New York par Deep Art Effects

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Biologie, sciences humaines, physique, chimie, politique, de l'infiniment petit à l'infiniment grand, il nous devient possible de trouver et de créer des relations qui sont au delà des capacités humaines, soit en termes de temps de réalisation, de capacité d'observation, de mémorisation ou simplement de persistance d'attention.

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Outils gratuits en IA.

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Free AI Writing, PDF, Image, and other Online Tools - TinyWow

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Free AI Writing, PDF, Image, and other Online Tools - TinyWow

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Future Tools - Find The Exact AI Tool For Your Needs

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FutureTools Collects & Organizes All The Best AI Tools So YOU Too Can Become Superhuman!

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ChatGPT : première interview radio de l'intelligence artificielle - L'invité de Sonia Devillers

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Interface de communication

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Contributors: John Schulman, Barret Zoph, Christina Kim, Jacob Hilton, Jacob Menick, Jiayi Weng, Juan Felipe Ceron Uribe, Liam Fedus, Luke Metz, Michael Pokorny, Rapha Gontijo Lopes, Shengjia Zhao, Arun Vijayvergiya, Eric Sigler, Adam Perelman, Chelsea Voss, Mike Heaton, Joel Parish, Dave Cummings, Rajeev Nayak, Valerie Balcom, David Schnurr, Tomer Kaftan, Chris Hallacy, Nicholas Turley, Noah Deutsch, Vik Goel, Jonathan Ward, Aris Konstantinidis, Wojciech Zaremba, Long Ouyang, Leonard Bogdonoff, Joshua Gross, David Medina, Sarah Yoo, Teddy Lee, Ryan Lowe, Dan Mossing, Joost Huizinga, Roger Jiang, Carroll Wainwright, Diogo Almeida, Steph Lin, Marvin Zhang, Kai Xiao, Katarina Slama, Steven Bills, Alex Gray, Jan Leike, Jakub Pachocki, Phil Tillet, Shantanu Jain, Greg Brockman, Nick Ryder, Alex Paino, Qiming Yuan, Clemens Winter, Ben Wang, Mo Bavarian, Igor Babuschkin, Szymon Sidor, Ingmar Kanitscheider, Mikhail Pavlov, Matthias Plappert, Nik Tezak, Heewoo Jun, William Zhuk, Vitchyr Pong, Lukasz Kaiser, Jerry Tworek, Andrew Carr, Lilian Weng, Sandhini Agarwal, Karl Cobbe, Vineet Kosaraju, Alethea Power, Stanislas Polu, Jesse Han, Raul Puri, Shawn Jain, Benjamin Chess, Christian Gibson, Oleg Boiko, Emy Parparita, Amin Tootoonchian, Kyle Kosic, Christopher Hesse

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We've trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.

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Une interface conversationnelle reliée au Web et qui donne des liens et cite ses sources.

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Perplexity is a free AI-powered answer engine that provides accurate, trusted, and real-time answers to any question.

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Mettre à la disposition de tous les meilleurs modèles de discussion d'IA de la communauté

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The first open source alternative to ChatGPT. 💪

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Tech giants Google, Microsoft and Facebook are all applying the lessons of machine learning to translation, but a small company called DeepL has outdone them all and raised the bar for the field.
Its translation tool is just as quick as the outsized competition, but more accurate and nuanced than any we've tried.

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DeepL Translate: The world's most accurate translator

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Translate texts & full document files instantly. Accurate translations for individuals and Teams. Millions translate with DeepL every day.

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Fast drawing for everyone. AutoDraw pairs machine learning with drawings from talented artists to help you draw stuff fast.

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Création d'images à partir de textes.

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Mixed Image Editing

A new way to combine real and synthetic images to create stunning works of art and photorealistic images bound only by your imagination.

Your Wish, Our Command

Edit Images As You Imagine

Step Outside the Box

Grow Images Beyond Their Edges

Fit Objects Into Any Scene

Sketch Your Ideas Into Reality

Team Up With Others

Piece Together Ideas

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Free AI image generator: Art, Social Media, Marketing | Playground

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Playground is a free-to-use online AI image creator. Use it to create art, social media posts, presentations, posters, videos, logos and more.

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Libérez votre créativité avec le pouvoir de Leonardo Ai.

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AI Image Generator - Create Art, Images & Video | Leonardo AI

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Envision The Extraordinary

Take creativity a step further with the transformative power of our Image Generation tool. It's not just about bringing your concepts to life - redefine the impossible. From beginners to professionals, we offer a spectrum of settings that can be intuitively tailored to your needs.

Discover an unprecedented fusion of simplicity and power, designed to cater to creative minds at all levels.

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Transform your projects with our AI image generator. Generate high-quality, AI generated images with unparalleled speed and style to elevate your creative vision

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Créez l'IA Art avec notre générateur d'images d'IA gratuit.

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Créez des images à partir de textes

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Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen
Engineering, Design, Product, and Prototyping
Jeff Belgum, Dave Cummings, Jonathan Gordon, Chris Hallacy, Shawn Jain, Joanne Jang, Fraser Kelton, Vishal Kuo, Joel Lehman, Rachel Lim, Bianca Martin, Evan Morikawa, Rajeev Nayak, Glenn Powell, Krijn Rijshouwer, David Schnurr, Maddie Simens, Kenneth Stanley, Felipe Such, Chelsea Voss, Justin Jay Wang
Comms, Policy, Legal, Ops, Safety, and Security
Steven Adler, Lama Ahmad, Miles Brundage, Kevin Button, Che Chang, Fotis Chantzis, Derek Chen, Frances Choi, Steve Dowling, Elie Georges, Shino Jomoto, Aris Konstantinidis, Gretchen Krueger, Andrew Mayne, Pamela Mishkin, Bob Rotsted, Natalie Summers, Dave Willner, Hannah Wong
Acknowledgments
Thanks to those who helped with and provided feedback on this release: Sandhini Agarwal, Sam Altman, Chester Cho, Peter Hoeschele, Jacob Jackson, Jong Wook Kim, Matt Knight, Jason Kwon, Anna Makanju, Katie Mayer, Bob McGrew, Luke Miller, Mira Murati, Adam Nace, Hyeonwoo Noh, Cullen O'Keefe, Long Ouyang, Michael Petrov, Henrique Ponde de Oliveira Pinto, Alec Radford, Girish Sastry, Pranav Shyam, Aravind Srinivas, Ilya Sutskever, Preston Tuggle, Arun Vijayvergiya, Peter Welinder

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DALL·E 2 is an AI system that can create realistic images and art from a description in natural language.

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Supprime les filigranes.

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Supprimer le filigrane - Uploader des images pour supprimer les filigranes translucides - Watermarkremover.io

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L'outil de suppression de filigrane vous permet de supprimer gratuitement les filigranes de vos images en quelques secondes seulement, sans inscription préalable.

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Génération de présentations en IA.

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Speed, meet quality. Tome helps you express ideas quickly without cutting corners or sacrificing subtlety. It's more engaging than a deck, and easier to build than a webpage.

Enter any prompt and create a compelling starting point for your presentation in minutes. It feels good to get work out of your head and into the world.

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Tome | Polished & Professional AI Presentations

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Tome is more engaging than a slide deck, and easier to build than a webpage. Use AI to quickly create multimedia presentations, microsites, and more.

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IROS 2022 Kyoto - la plus grande conférence au Japon // Robots et technologies du futur

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Enchanted Tools — Presentation of Miroki, our prototype Robot & Character (FULL VERSION)

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De nombreuses vidéos sur la programmation du mBot et du mBot 2.

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Depuis 2018 , le Département du Val d’Oise s’inscrit dans une politique volontariste d’accompagnement et d’échange sur l’innovation pédagogique dans ses collèges. A ce titre, il a fait de la robotique un nouveau levier d’impulsion innovante qui s’est traduit notamment par la mise en place de compéti…

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Création d'avatars en IA.

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Transform photos into AI video presenters at scale. Produce AI-powered, cost-effective videos for training materials, internal communications, marketing and more, at the touch of a button.

videos created since 2021

Experience AI video creation on the go with D-ID's Creative Reality™ Studio Mobile App. Animate faces and create digital people right from your phone, and take your content to the next level. Available now on the App Store and Google Play.

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images and text at the click of a button.

Use the latest generative AI tools to create talking avatars at a click of a button using the Creative Reality™ Studio.

Supercharged with Stable Diffusion and GPT-3, the self-service studio lets you turn your ideas into stunning videos that are personalized, cost-effective and engaging.

Reduce the cost and hassle of video production, at scale, in over 100 languages, with zero technical knowledge.

chat.D-ID is a web app that uses real-time face animation and advanced text-to-speech to create an immersive and human-like conversational AI experience. The free app lets you speak face-to-face with ChatGPT.

D-ID's API is robust, massively scalable and super simple to use - integrate it in just four lines of code. It now also supports streaming generation of talking head AI videos from an image and audio file. Build a whole ecosystem around our platform. The possibilities are endless.

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Press Release: D-ID and Multiverse Partners Join Forces to Bring AI Avatars to Life Globally

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Press Release: D-ID Launches Creative RealityTM Studio Mobile App Enabling AI Video Generation On the Go

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TechCrunch: D-ID's new mobile app uses AI to make videos from photographs

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AdChat DFW: Vantage Innovation Lab Revolutionizes Marketing with Historic AI Voice Activation

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D-ID, the leading AI Video Creation Platform, helps you make photorealistic videos using generative AI via D-ID's API or Creative Reality™ studio.

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DANE de Créteil : ROBOCUP Junior 2022-2023

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DANE de Créteil : ROBOCUP Junior 2022-2023

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La RoboCup Junior Open Île-de-France est un concours qui s'adresse aux jeunes de 9 à 19 ans. Ce concours de robotique constitue un dispositif pédagogique interdisciplinaire qui permet aux participants de découvrir la robotique ainsi que les métiers qui y sont liés.

FLYER ROBOCUP JUNIOR 2022-2023

Inscription au concours avant le 9 décembre 2022

La Robocup Junior s'adresse aux jeunes dès la moyenne section, et jusqu'à 19 ans. Les inscriptions des équipes mixtes de 2 à 5 élèves (suivant la ligue) se font en ligne sur la plateforme Magistère jusqu'au 9 décembre 2022

Accès à Magistère de l'académie de Paris

Pour accéder au parcours et à l'inscription :
1 Indiquez que vous n'êtes pas de l'académie de Paris / 2 Sélectionnez l'académie de Créteil / 3 Saisissez vos identifiants professionnels

Les meilleures équipes inter-académiques seront qualifiées pour la finale nationale qui se déroulera à Bordeaux les 13 et 14 mai 2023 et pourront ainsi prétendre à une qualification pour la finale européenne en Croatie du 11 au 17 juin 2023.

La compétition internationale RoboCup et RoboCup junior aura lieu au Parc des Expositions de Bordeaux, du 3 au 9 juillet 2023

Le règlement actuellement en vigueur date de 2022. Des modifications sont susceptibles d'être faites pour l'édition 2023 : elles seront publiées sur cette page.

Un tournoi international de robotique

La RoboCup a été proposée en 1996, par Hiroaki Kitano, afin de de stimuler la recherche en matière de robotique et d'intelligence artificielle au travers d'un objectif ambitieux : mettre au point une équipe de robots totalement autonomes capables de vaincre l'équipe humaine, championne du monde de football en 2050.

Ce tournoi international réunit tous les ans des milliers de participants formant des centaines d'équipes venant d'une cinquantaine de pays. C'est l'un des événements scientifiques et technologiques de niveau international parmi les plus importants en matière de recherche et de formation.

Ses atouts sont multiples :

Un projet international d'envergure en matière de recherche et de formation ;

Un projet interdisciplinaire qui favorise le croisement de différentes disciplines : mathématiques, arts plastiques, technologie, EPS, éducation musicale, anglais..

Une aventure humaine qui permet de travailler en équipe, de découvrir la compétition, de rencontrer et d'échanger avec les autres participants et de résoudre collectivement des problèmes.

Un projet pédagogique motivant qui permet aux élèves de développer leurs compétences et leurs connaissances. Les objectifs pédagogiques généraux consistent en effet à favoriser l'intérêt, la pratique et la connaissance des sciences afférentes, notamment : l'informatique, le codage, l'algorithmique et l'internet des objets.

L'épreuve Rescue : le robot doit suivre un parcours semé d'embûches

Une équipe pour accompagner les enseignants

Dans chaque académie, une équipe est disponible pour répondre aux différentes questions. Elle propose des animations et formations afin de mieux préparer votre projet.

Les équipes de formateurs de la DANE de Créteil sont présentes pour vous accompagner. Une formation de trois demi-journées est proposée pour préparer les équipes au concours, c'est-à-dire à l'épreuve technique mais aussi de présentation.

Vous pouvez également compter sur le dispositif PreMat de la DANE de Créteil qui met du matériel à disposition des équipes désireuses de participer au concours.

La préparation au concours est une véritable activité en mode projet comme le montre cette courte vidéo proposée par les élèves du collège Pablo Neruda à Aulnay- sous-Bois, dont l'équipe Dark GS9 a remporté la seconde place de la Ligue Soccer en 2022.

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La RoboCup Junior Open Île-de-France est un concours qui s'adresse aux jeunes de 9 à 19 ans. Ce concours de robotique constitue un dispositif pédagogique interdisciplinaire qui permet aux participants de découvrir la robotique ainsi que les métiers qui y sont liés.

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Voici des compléments au règlement de la Robocup Junior pour 2022/2023.

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Présentation de la compétition

National et international 2023
Présentation de la compétition Concours national - Finale France - Bordeaux
13-14 mai 2023 à l'occasion de la foire Internationale de Bordeaux
CROATIE

La finale européenne sera organisée par la Croatie, à VARAZDIN du 7 au 10 Juin 2022

ROBOCUP 2023

ROBOCUP 2023

La finale internationale sera organisée cette année à BORDEAUX
Etat des lieux de la compétition 2023
138 équipes au total (66 en 2022)

Cela représente environ 663 élèves au total.

- 54 Discovery (écoles primaires)

Organisation de l'Open Ile de france

3 épreuves, 3 organisations

SOCCER

ON STAGE

RESCUE LINE

Modalités d'organisation en cas d'impossibilité en raison des règles sanitaires

Règlements et grilles d'évaluation

SOCCER

RESCUE LINE

ON STAGE

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Présentation de la compétition National et international 2023 Présentation de la compétition Concours national - Finale France - Bordeaux 13-14 mai 2023 à l'occasion de la foire Internationale de Bordeaux CROATIE La finale européenne sera organisée par la Croatie, à VARAZDIN du 7 au 10 Juin 2022 ROBOCUP 2023 ROBOCUP 2023 La finale internationale sera organisée cette année à BORDEAUX Etat des lieux de la compétition 2023 138 équipes au total (66 en 2022) Cela représente environ 663 élèves au total.

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Nos élèves à la Cybertech 2022 - Collège International

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Les élèves, futurs adultes, vont sans doute vivre dans un monde dans lequel ils seront de plus en plus confrontés aux systèmes automatisés et aux robots, on peut même dire que c’est déjà un peu le cas. De plus, dans le cadre des programmes du cours de Technologie, les élèves de 3ème doivent réaliser de[...]

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Le collège International à la Robocup Junior 2022

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Le collège International à la Robocup Junior 2022

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Qu'est-ce que la Robocup junior? La Robocup Junior est un concours de robotique international ouvert aux jeunes de 11 à 19 ans. L'Open Ile de France qui a eu lieu le 13 avril 2022 à la Cité des Sciences et de l'industrie à Paris regroupait les participants des académies de Paris, Créteil et Versailles, dont[...]

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Les photos de la finale nationale à Bordeaux 2022

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Les photos de la finale nationale à Bordeaux 2022

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L’ingénierie brillante des roues Mecanum -

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The Crabster - A Giant Robotic Crab that can do Specific Task

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Maqueen Plus Advanced Tutorial

Designed for secondary school students with certain coding experience, this Maqueen Plus Advanced Tutorial contains 7 projects and 19 tasks. Clear and complete structures are arranged in every task such as, hardware function, material list, connection, knowledge field, project practice, etc., which can be directly used for classroom teaching.
In the course, we combine HUSKYLENS with Maqueen Plus and Maqueen Mechanic Kit. Each task is independent but interconnected in the content. For example, in the project Vehicle Sharing there are three tasks: Unlock Maqueen Plus with Face, Pricing, and Set A Flag Bit to Realize Charging Reset. Each task realizes a function separately and the main project can be done when completing the functions of three tasks.
Meanwhile, we choose Mind+ graphical programming, which allows students to implement complex projects through simple graphical programming languages.

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DFRobot Education- online resources for STEM and maker education

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DFRobot Education is a platform to empower creation for teachers and learners. From projects, tutorials to curriculums, get inspired with quality-assured resources for STEM and maker education, start creating with tools and technologies including Arduino, Python, Scratch, AI and IoT.

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Site en Anglais sur la programmation du Maqueen +

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Site en Anglais sur la programmation du Maqueen +

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Robotics: How-to Build your own Robot – Wagner’s TechTalk

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If you have ever wanted to assemble your own Robot, teach it new tricks but not sure where to start – you’ve found the right spot. On this page, I’ll show you how you can easily get started with the DFRobot Maqueen Plus robot. Don’t worry, you won’t have to learn any complicated programming and yo…

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La France autorise les voitures autonomes

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La France autorise les voitures autonomes

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Yann Arnaud (Macif) : La France autorise les voitures autonomes à rouler

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Fait avec ❤️ dans Microsoft MakeCode for micro:bit.

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Contrôle PID pour Maqueen Plus : vitesse des deux moteurs

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Contrôle PID pour Maqueen Plus : vitesse des deux moteurs

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Contrôle PID pour Maqueen Plus : vitesse des deux moteurs

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Fait avec ❤️ dans Microsoft MakeCode for micro:bit.

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1. Introduction

HuskyLens is an easy-to-use AI machine vision sensor with 7 built-in functions: face recognition, object tracking, object recognition, line tracking, color recognition, tag recognition and object classification.

Through the UART / I2C port, HuskyLens can connect to Arduino and micro:bit to help you make very creative projects without playing with complex algorithms.

2. Specification

Processor: Kendryte K210

Image Sensor: OV2640 (2.0Megapixel Camera)

Supply Voltage: 3.3~5.0V

Current Consumption(TYP): 320mA @ 3.3V, 230mA @ 5.0V (face recognition mode; 80% backlight brightness; fill light off)

Interr: UART; I2C

Display: 2.0-inch IPS screen with 320*240 resolution

Built-in Algorithms: Face Recognition, Object Tracking, Object Recognition, Line Tracking, Color Recognition, Tag Recognition, Object Classification

Dimension: 52mm x 44.5mm (2.05*1.75 inch）

3. Board Overview

3.1 Connectors

USB Connector: power supply for Huskylens; connect to the computer to upgrade the firmware

4pin Connector in UART Mode

4pin Connector in I2C Mode

You can connect either USB port or 4pin port to power HuskyLens.

Due to the onboard power supply automatic switching circuit, the USB port and the 4pin port can be connected to the power supply at the same time, and the power supply on the USB port is used first.

Please ensure that the supply voltage and rate are sufficient to prevent HuskyLens from working abnormally.

3.2 Buttons

There are two buttons on the HuskyLens, the function button and the learning button. The basic operations of these two buttons are shown as follows:

Dial the "function button" to left or right to switch different functions.

Short press the "Learning button" to learn the specified object; long press the "Learning button" to continuously learn the specified object from different angles and distances; if HuskyLens has learned the object before, short press the "Learn button" to make it forget.

Long press the "function button" to enter into the second-level menu(parameter setting) in the current function. Dial left, right or short press the "function button" to set related parameters.

4. Upgrade Firmware

Before using this product, it is strongly recommended to upgrade HuskyLens' firmware to the latest version to get the latest functions and the most stable experience. If your HuskyLens already has the latest firmware, no update is required. We recommand to upload the firmware on windows 10 using the HuskyLens Uploader since it features a GUI, and easy-to-use.

The firmware version required for this tutorial is not lower than V0.5.1a. This version integrates all functions (including object classification).

How to check the firmware version?

1. Dial the function button to the right until the last option "General Settings", short press the function button to enter the secondary menu.

2. Dial the function button to the right until you reach the "version" option, you can see the version number. As shown in the figure below, the version number is: 0.5.1Norm.

4.1 In Windows

We recommand to upload the firmware on windows 10 using the HuskyLens Uploader. It is easy and convenient.The steps are shown below:

1. Download the HuskyLens Uploader. Click here to download it.

2. Download the USB to UART driver, and install it. Click here to download it.
HuskyLesn adopts the CP2102N chip to implement the USB to serial port function. After the driver is installed, you can use the microUSB cable to connect the USB port of HUSKYLENS to the computer's USB port. At this time, open the device manager and there should be a COM port whose name starts with "Silicon Labs CP210x". As shown below:

1. Download the latest firmware. Click here to download the V0.5.1a.Click here to check the firmwares of all versions.

2. Run the HuskyLens Uploader, a small black cmd window will pop up first, and after a while, the interface window will appear, then click the "Select File" button to load the firmware.

Click the "Upload" button. Wait about 5 minutes to complete the uploading. The firmware file is large, so it may take a little bit time. After the uploading is completed, the prompt text "Uploading" will disappear and the HuskyLens screen will light up. Please do not close the interface window and the small black cmd window during uploading.

If you are prompted to enter Huskylens' COM port Manually, you need to manually enter the HuskyLens' COM port mapped on your computer. The COM port number can be found in the device manager.

If the firmware uploading fails or the HuskyLens' screen does not light up, or other strange phenomenas, such as invalid buttons, HuskyLens can not learn, etc. you can try to click the "Reset Memory" button. After a while, the two fill lights of HUSKYLENS will light up, and HuskyLens has been reset. Please refer to the above steps and re-upload the firmware.

4.2 In Linux or Mac

In this section, we take ubuntu 18.04.4 as an example to show you how to upgrade Huskylens firmware on Linux or Mac. These steps are shown as follows:

1. Download the USB to UART driver, and install it. Click here to download it.

HuskyLesn adopts the CP2102N chip to implement the USB to serial port function.

In Ubuntu 18.04.4, the USB serial port of HuskyLens can be directly identified when plugged in, so the driver is not required to be installed.

2. Download the latest firmware and kflash.py script. Click here to check them.

You can clone the entire repository of "HuskyLens / HUSKYLENSUploader" to your computer by git command.

3. Install pip3 first if you do not have it in your OS.

sudo apt install python3-pip

Install pip3 on MAC

 /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)" brew install python3

4. Run the following script to install pyserial.

sudo pip3 install pyserial

5. Go to the HUSKYLENSUploader folder.

cd HUSKYLENSUploader

6. According to the actual firmware version, enter the full name of the firmware in the following script. Take V0.5.1 version firmware as an example, run the following script to upload the firmware:

sudo python3 kflash.py -b 2000000 HUSKYLENSWithModelV0.5.1Norm.kfpkg

7. Upgrade has been completed now. Enjoy it.

5. General Settings

5.1 Basic Operation

The basic operation is shown as follows:

1. Select the general settings: Dial the function button right until the words "General Settings" is displayed at the top of the screen, then select it.

2. Enter the general setting mode: Short press the function button to enter it.

1. Select and adjust the parameter: Dial the function button left or right to select different parameter, then short press the function button to enter the parameter. Dial the function button left or right to adjust the parameter. Then short press the function button again to confirm the parameter.

2. Save the settings: After adjusting the parameters, dial the function button left to select "Save & Return", then short press the function button. A message "Do you save data?" will appear. The default seletion is "Yes". At this time, short press the funtion button to save and exit.

The parameters in the general settings are all selected and adjusted by dialing "function button" left or right, and pressing the "function button".

After setting the parameters, be sure to select "save and return" to save the set parameters.

5.2 Parameters Introduction

There are 10+ different parameter settings in the general settings.

6. Color and Coordinate

6.1 Color Instructions

In each function, the color definitions of the frame and the symbol "+" in the center of the screen are all the same, which helps you know the current status of HuskyLens.

The RGB LED indicator is used to indicate the status of the face recognition function. Its colors are defined as follows.

6.2 Coordinate System

When HuskyLens is detecting a object, the target will be automatically selected by a color frame on the screen. The coordinates of the color frame position x and y are assigned according to the following coordinate system. After getting the coordinates from the UART / I2C port, you can know the position of the object.
Format:（x,y）
7. Functions Introduction

7.1 Face Recognition

This function can detect any face contour, recognize and track the learned face.

7.1.1. Recognize one face

The default setting is to learn and recognize a single face.

Operation and Setting

Dial the function button to the left until the word "Face recognition" is displayed at the top of the screen.

Learning and Detection

1. Face Detection: Point the HuskyLens at any faces. When a face is detected, it will be automatically selected by a white frame with words "Face" on the screen.

If you want HuskyLens to learn or recognize your face, that is, take a selfie, you can't see the screen at this time, you can determine the status according to the different colors of the RGB indicator.

2. Face Learning: Point the "+" symbol at a face, short press the "learning button" to learn the face. If the same face is detected by HuskyLens, a blue frame with words "Face: ID1" will be displayed on the screen，which indicates that HuskyLens has learned the face and can recognize it now.

However, HuskyLens only learned one plane (one-dimensional) of the face after the above operation, while human face is three-dimensional. If the angle of the face has been changed, HuskyLens may not recognize it. So you need to let HuskyLens learn a face from its different angles.

The operation shows as follows：(Before HuskyLens learning news thing, please let it forget the former things first.)

Keep pressing the "learning button", point HuskyLens' "+" symbol at different angles of the face. During this process, a yellow frame with words "Face: ID1" will be displayed on the screen, which indicates HuskyLens is learning the face. Please point the yellow frame at different angles of the same person's face, such as front face and side face (or multiple photos of the same person), to enter all angles of this person's face.

Then you can release the "learning button" to finish the learning. When Huskylens detected the learned face, a blue frame with words "Face: ID1" will be displayed, now HuskyLens can recognize the face from different angles.

If there is no "+" symbol in the center of the screen, it means that the HuskyLens has already learned the face in the current function, now HuskyLens is detecting it. If you want to let HuskyLens learn a new face, you have to make it forget the learned face first.

3. Face Recognition: The learned face information will be automatically saved. When HuskyLens detects the learned face, this face will be selected by a blue frame and identified as face: ID1. The size of the frame will change with the size of the face, and the face will be tracked automatically.

4. Forget the Learned Face: If there is no "+" symbol in the center of the screen, it means that the HuskyLens has already learned the face in the current function. If you want to recognize another face, or re-enter face information, you need to delete the current face information.

When HuskyLens is in the face recognition mode, short press the "learning button", the screen will display "click again to forget". Before the countdown ends, short press the "learning button" again to delete the learned face information, then the yellow "+" symbol is displayed. Now you can let HuskyLens learn a new face.

The operation of forgetting is totally the same in other functions. Therefore, this operation will not be repeated in subsequent chapters.

7.1.2. Recognize multiple faces

The default setting is to learn a single face. In order to learn multiple faces, we need to enable "Learn Multiple" of face recognition.

Operation and Setting

1. Dial the function button to the left until the word "Face recognition" is displayed at the top of the screen.

2. Long press the function button to enter the parameter setting of the face recognition function.

3. Dial the function button until "Learn Multiple" is displayed, then short press the function button, and dial to the right to turn on the "Learn Multiple" switch, that is, progress bar turns blue and the square icon on the progress bar moves to the right. Then short press the function button to confirm this parameter.

4. Dial the function button to the left until "Save & Return" shows. And the screen prompts "Do you want to save the parameters?" Select "Yes" in default, now short-press the function button to save the parameters and return automatically.

Learning and Detection

1. Multiple Faces Learning: Point the "+" symbol at the face, long press the "learning button" to learn the face of the first person. Then release the "learning button", a blue frame with words "Face: ID1" will be displayed if HuskyLens detects the same face，meanwhile, a message "Click again to continue! Click other button to finish" will be displayed. Please short press the "learning button" before the countdown ends if you want to learn the face of other person. If not, short press the "function button" before the countdown ends, or do not press any button to let the countdown ends.

In this chapter, we will learn the next face continuously. So we need to short press the "learning button" before the countdown ends. Then we can let HuskyLens learn the face of the second person. The same as the steps to recognize the first face, point the "+" symbol at the second face, long press the "learning button" to learn the face of the second person. Then release the "learning button", a blue frame with words "Face: ID2" will be displayed if HuskyLens detects the same face.

The face ID is the same as the order of entering the face, that is: the learned faces will be marked as "face: ID1", "face: ID2", "face: ID3" in order, and different face IDs correspond to different color frames.

If there is no "+" symbol in the center of the screen before learning, it means that the HuskyLens has already learned, now HuskyLens is detecting face. If you want to let HuskLens learn new face, you need to let HuskyLens forget the learned face first.

Please turn to the 7.1.1. Learn one face to check the way to forget the learned face.

2. Multiple Faces Recognition: The learned face information will be saved automatically. When HuskyLens detects the learned face from multiple faces, the learned face will be selected with a frame and identified by the message face: IDx. For example, when HuskyLens detects the learned face of the first person, it will be selected with a blue frame and identify face: ID1; when HuskyLens detects the learned face of the second person, it will be selected with a yellow frame and identify face: ID2; and so on.

The color of the frame corresponding to different face IDs is also different, and the frame size will change with the size of the face, and the face will be automatically tracked.

7.2 Object Tracking

This function can learn and track a specified object. Only one object can be tracked, and multiple objects are not supported.

Operation and Setting

Dial the function button to the left or right until the word "Object Tracking" is displayed at the top of the screen.

1. Long press the function button to enter the parameter setting of the object tracking function.

2. Dial the function button to the right to select "Learn Enable", then short press the function button, and dial it to the right to turn the "Learn Enable" ON, that is, the square icon on the progress bar is turned to the right. Then short press the function button to confirm this parameter.

3. The method to turn on the switch of saving models automatically is the same as before. According to the steps above to switch "Auto Save" ON.

1. You can also adjust the size of the frame by setting "Frame Ratio" and "Frame Size" to match the shape of the object.

2. Dial the function button to the left to select "Save & Return", and short press the function button to save the parameters and return automatically.

Learning and Detection

1. Object Learning: Point Huskylens to the target object, adjusting the distance and until the object is included in the yellow frame of the center of the screen. Then long press "learning button" to learn the object from various angles and distances. During the learning process, the yellow frame with words "Learning: ID1" will be displayed on the screen.

When HuskyLens can track the object at different angles and distances, you can release the "learning button" to complete the learning.

2. Object Tracking: Move the HuskyLens or the target, the frame will track the target automatically. When tracking the object, the yellow words "Learning: ID1" will be displayed, indicating that HuskyLens is tracking the object while learning. This setting improves the object tracking ability.

When the recognition result meets the requirements, you can turn off "Learn Enable".

Only one object can be tracked at a time. It can be any object with a clear outline, even various gestures.

7.3 Obejct Recognition

This function can recognize what it is, and track it.

HuskyLens can recognize 20 built-in objects. They are aeroplane, bicycle, bird, boat, bottle, bus, car, cat, chair, cow, dining-able, dog, horse, motorbike, person, potted lant, sheep, sofa, train, TV.

Object recognition cannot distinguish the difference between objects of the same type. For example, it can only recognize that this is a cat, but it cannot recognize what kind of cat it is. Different from face recognition, people are one type, but different faces can be distinguished.

The default setting is to recognize a single object. This chapter uses marking and recognizing multiple objects as an example to demonstrate.

Operation and Setting

1. Dial the function button to the left or right until the word "Obejct Recognition" is displayed at the top of the screen.

2. Long press the function button to enter the parameter setting of the object recognition function.

3. Dial the function button to the left until "Save & Return" shows. And the screen prompts "Do you want to save the parameters?" Select "Yes" in default, now short-press the function button to save the parameters and return automatically.

Learning and Detection

1. Object Detection: When detecting objects, HuskyLens will automatically recognize it, and the object will be displayed by the white frame with its name on the screen.

At present, only 20 built-in objects can be recognized, and the remaining objects cannot be recognized temporarily.

2. Object Mark: Point the "+" symbol at the object, then short press the "learning button", the color of the frame changes from white to blue, and the name of the object and it's ID1 will appear on the screen, meanwhile, a message "Click again to continue! Click other button to finish" will be displayed. Please short press the "learning button" before the countdown ends if you want to mark the next object. If not, short press the "function button" before the countdown ends, or do not press any button to let the countdown ends.

3. Object Recognition: When encountering the learned objects, they will be selected by the color frame, and the name and ID number will be displayed. When encountering new ones, the selection frame is white.

The ID number is related to the order of marking objects. For example, if a dog is marked for the first time and a cat is marked for the second time, when the dog is recognized, the words "dog: ID1" will be displayed on the screen; and when the cat is recognized, the words "cat: ID2" will be displayed on the screen.

This can be used as a simple filter to find out what you need from a bunch of objects.

7.4 Line Tracking

This function can track specified color lines and make path predictions. The default setting is to track only one color line.

In this chapter, we use tracking one color line as an example to demonstrate.

Operation and Setting

1. Dial the function button to the left or right until the word "Line Tracking" is displayed at the top of the screen.

2. Long press the function button to enter the parameter setting of the line tracking function.

3. Dial the function button right or left until "Learn Multiple" is selected, then short press the function button, and dial it to the left to turn off the "Learn Multipe" switch, that is, the square icon on the progress bar is turned to the left. Then short press the function button to complete this parameter.

1. You can also turn on the LEDs by setting "LED Switch". This is very useful in the dark environment.

2. Dial the function button to the left until "Save & Return" is selected, and short press the function button to save the parameters and it will return automatically.

Learning and Detection

1. Line Learning: It is recommended that within the view field of HuskyLens, just remain line to learn and no any cross lines. Point the "+" symbol at the line. Then HuskyLens will automatically detect the line and a white arrow will appear on the screen.

At that time, short press the "learning button" to complete the learning process. A blue route direction arrow will appear on the screen.

2. Line Prediction: When HuskyLens detects the line which has been learned, a blue arrow will appear automatically on the screen. The direction of the arrow indicates the predicted direction of the line.

When learning the line, we need to adjust the position of HuskyLens to be parallel to the line.

Huskylens can learn multiple lines according to the color of lines, but these lines must be monochrome lines with obvious color that different from the background.

In most cases, the color of tracking line is only one. Therefore, in order to ensure stability, we recommend to track the single color line.

The color of the lines has a lot to do with the ambient light, so please try to keep the ambient light as stable as possible.

7.5 Color Recognition

This function can learn, recognize, and track the specified color.

The default setting is to learn, recognize, and track a single color. This chapter uses learning, recognizing, and tracking multiple colors as an example to demonstrate.

Color recognition is greatly affected by ambient light. Sometimes HuskyLens may misidentify similar colors. Please try to keep the ambient light unchanged.

Operation and Setting

1. Dial the function button to the right or left until the word "Color Recognition" is displayed at the top of the screen.

2. Long press the function button to enter the parameter setting of the color recognition function.

3. Dial the function button to the left until "Save & Return" shows. And the screen prompts "Do you want to save the parameters?" Select "Yes" in default, now short-press the function button to save the parameters and return automatically.

Learning and Detection

1. Color Detection: Point the icon "+" in the center of the HuskyLens screen to the target color block, and a white frame will appear on the screen, which selects the target color block automatically. Adjust the angle and distance of the HuskyLens to the color block so that the white frame can include the entire target color block as far as possible.

2. Color Learning: Point the "+" symbol at the first color block, and long press the "learning button". A yellow frame will be displayed on the screen, indicating that HuskyLens is learning the color. At this time, adjust the distance and angle between HuskyLens and the color block, to let HuskyLens learn the color block in various distances and angles. Then, release the "learning button" to complete learning the first color block, meanwhile, a message "Click again to continue! Click other button to finish" will be displayed. Please short press the "learning button" before the countdown ends if you want to learn other color blocks. If not, short press the "function button" before the countdown ends, or do not press any button to let the countdown ends.

3. Color Recognition: When encountering the same or similar color blocks, some color frames with IDs will be automatically displayed on the screen, and the size of the frames are same as the size of the color blocks.

The ID number is related to the order of learned color. For example, if a yellow block is marked for the first time and a green block is marked for the second time, when the yellow block is recognized, the words "Color: ID1" will be displayed on the screen, and when the green block is recognized, the words "Color: ID2" will be displayed on the screen.

In the firmware below V0.5.1, when there are multiple same or similar color blocks appear at the same time, the other color blocks cannot be selected, that is, only one color block can be recognized at each time.

In firmware version V0.5.1 and above, this function is optimized. when there are multiple same or similar color blocks appear at the same time, these color blocks can be recognized and selected at the same time. This function can be used to count the color blocks.

Count Color blocks

In firmware V0.5.1 and above, HUSKYLENS can count the color blocks in the color recognition function, that is, calculate the number of color blocks in the HUSKYLENS screen. The following is an example of recognizing multiple balloons of similar colors.
1. Learn and Recognize Colors
Point the "+" symbol at the target balloon, then press the "learning button" to learn the color of the balloon, and then release the "learning button" to complete the learning. You can see that the color of the balloon can be recognized , but for balloons with similar colors, it may not be able to identify them.
2. Adjust the Threshold
When recognizing color blocks of similar colors, the recognition accuracy can be adjusted by setting the threshold. For example, in the figure above, some yellow balloons with similar colors are not recognized, and the threshold may be set higher. In the parameter setting of the color recognition function, there is the "Block Sized Threshold" parameter. The lower the value of this parameter, the lower the accuracy, but the more similar color blocks can be recognized. As shown in the figure below, when the threshold is 20, only one yellow ball can be recognized, and when the threshold is 0, all three yellow balls can be recognized. Please adjust the threshold according to the actual effect, so that the recognition accuracy is within your acceptable range.

With this function, you can easily obtain the number of yellow balls on the screen in real time.

7.6 Tag Recognition

This function can detect tags, and learn, recognize, track specified tags. These tags are called April Tags. Click here to download more April Tags.

Tips: Only April Tags can be regonized.

The default setting is to learn a single tag. This chapter uses learning, recognizing, and tracking multiple tags as an example to demonstrate.

Operation and Setting

1. Dial the function button to the right or left until the words "Tag Recognition" is displayed at the top of the screen.

2. Long press the function button to enter the parameter setting of the tag recognition function.

3. Dial the function button until "Learn Multiple" is displayed, then short press the function button, and dial to the right to turn on the "Learn Multiple" switch, that is, progress bar turns blue and the square icon on the progress bar moves to the right. Then short press the function button to confirm this parameter.

Dial the function button to the left until "Save & Return" shows. And the screen prompts "Do you want to save the parameters?" Select "Yes" in default, now short-press the function button to save the parameters and return automatically.

Learning and Detection

You can use the following tags to test this function.

1. Tag Detection: When Huskylens detects the tag, the tag will be automatically selected by the white frame on the screen.

2. Tag Learning: Point the "+" symbol at the first tag, and press the "learning button". A yellow frame with words "Tag:ID1" will be displayed on the screen, indicating that HuskyLens is learning the tag now. Then, release the "learning button" to complete learning the first tag, meanwhile, a message "Click again to continue! Click other button to finish" will be displayed. Please short press the "learning button" before the countdown ends if you want to learn other tags. If not, short press the "function button" before the countdown ends, or do not press any button to let the countdown ends.

3. Tag Recognition When encountering the learned tag, some color frames with IDs will be automatically displayed on the screen. The size of the frames changes with the size of the tags, and the frames automatically track these tags.

7.7 Object Classification

This function can learn multiple photos of different objects, and then use the built-in machine learning algorithm for training. After the training is completed, when the learned objects appear again in the HuskyLens' camera, HuskyLens can recognize them and display their ID numbers. The more HuskyLens learns the photos of the same object, the more accurate the recognition can be.

The default setting is to learn multiple objects. This chapter uses recognizing whether a worker wears a helmet as an example to demonstrate.

Operation and Setting

1. Dial the function button to the right or left until the words "Object Classification" is displayed at the top of the screen.

2. Long press the function button to enter the parameter setting of the object classification function.

3. Dial the function button to the left until "Save & Return" shows. And the screen prompts "Do you want to save the parameters?" Select "Yes" in default, now short-press the function button to save the parameters and return automatically.

Learning and Detection

You can use the following picture to test.
1. Object Learning:
Point the large frame at the first target object(the worker with a helmet on the left in the picture above), and long press the "learning button", a yellow frame with words "Learning XX/30 ID:1" will be displayed on the screen, indicating that HuskyLens is learning the object now. Adjust the distance and angle, let HuskyLens learn the object in various distances and angles. Then, release the "learning button" to complete learning the first object, meanwhile, a message "Click again to continue! Click other button to finish" will be displayed. Please short press the "learning button" before the countdown ends if you want to learn other objects. If not, short press the "function button" before the countdown ends, or do not press any button to let the countdown ends.

In this chapter, you need to continue to learn the next object (the worker without a helmet on the right in the above picture), so press the "learning button" before the countdown ends, and then point the large frame at the second target object, long press the "learning button" to complete the learning of the second object. And so on.

The order of the object ID and the learned object is the same, that is: the learned objects will be marked as "object: ID1", "Object: ID2", "Object: ID3", and so on, and the color of the frame corresponding to the object is also different.
2. Object Recognition:
When HuskyLens encounters the learned object again, its ID number will be displayed on the screen. As shown in the figure below, when HuskyLens recognizes that the worker is wearing a helmet, the screen displays ID1, and if there is no helmet, it displays ID2.

More interesting ideas based on object classification: https://community.dfrobot.com/makelog-308212.html

7.8 Auxiliary Function

In firmware V0.5.1 and above, more auxiliary functions are added to help you use HUSKYLENS to set up projects better.

7.8.1 Customize the ID Name

You can change the corresponding name of the ID, for example: change "Face:ID1" to "Jack:ID1", and "Color:ID1" to "Red:ID1". This function is used to name a people or object, and make the result of recognition more recognizable. All 6 algorithms support customizing the ID name except line tracking. And only English names are supported.

Demonstration: Change the name of ID1 to Jack in face recognition

Mind+ Sample Program:

MakeCode Sample Program:

Arduino Sample Program:

#include "HUSKYLENS.h" HUSKYLENS huskylens; void setup() { Serial.begin(115200); Wire.begin(); while (!huskylens.begin(Wire)) { Serial.println(F("Begin failed!")); delay(100); } while (!huskylens.setCustomName("Jack",1)) // bool setCustomName(String name,uint8_t id) { Serial.println(F("ID1 customname failed!")); delay(100); } } void loop() { }

Result

"Jack:ID1" will be shown on screen after HUSKYLENS learning the first face ID1. As shown below:

7.8.2 Displaying Customized Text on the Screen

The onboard screen can be used to display texts anywhere on itself. It supports English characters, numbers and symbols. The recognition results and data from sensors can be directly displayed on the screen. All 7 algorithms support the customized text.

Demonstration: Displaying "Mind+" on the upper right corner at coordinates of (230,35)

Mind+ Sample Program:

MakeCode Sample Program:

Arduino Sample Program:

#include "HUSKYLENS.h" HUSKYLENS huskylens; void setup() { Serial.begin(115200); Wire.begin(); while (!huskylens.begin(Wire)) { Serial.println(F("Begin failed!")); delay(100); } while (!huskylens.customText("mind+",230,35)) // bool customText(String text,uint16_t x,uint8_t y) { Serial.println(F("custom text failed!")); delay(100); } } void loop() { }

Result

7.8.3 Saving the Photos or Screenshots into SD Card

Like a digital camera, HUSKYLENS can take photos or screenshots, and save them on an SD card. With an onboard SD card slot on HUSKYLENS, you can just plug in the SD card and use it. The screenshots contain the texts, frames displayed on the screen, while the photos contain only the image.

All 7 algorithms support this function. An SD card is required when using this function.

First-line brands, such as SanDisk, Toshiba, Samsung, and Kingston are recommended. Incompatibility problems may exist between SD cards of small brands.

The images saved by HUSKYLENS is with resolution ratio of 320*240. And it is unchangeable.

Please format the SD card as FAT32. Taking photos and screenshots, and saving them costs some time. So, it is recommended to use this function at least 0.5 seconds apart.

The SD card slot is facing inwards, so, the SD card should be inserted outwards as shown below:

Demonstration: Press button A of micro:bit or pull down the Arduino Pin A0, then HUSKYLENS will take a screenshot and save it in SD card

Mind+ Sample Porgram:

MakeCode Sample Porgram:

Arduino Sample Porgram:

#include "HUSKYLENS.h" HUSKYLENS huskylens; void setup() { Serial.begin(115200); pinMode(A0,INPUT_PULLUP); Wire.begin(); while (!huskylens.begin(Wire)) { Serial.println(F("Begin failed!")); delay(100); } } void loop() { if(digitalRead(A0) == 0) { while (!huskylens.saveScreenshotToSDCard()) // bool saveScreenshotToSDCard() or bool savePictureToSDCard() { Serial.println(F("save screenshot to SD card failed!")); delay(100); } Serial.println(F("saving screenshot to SD card...")); delay(500); // The interval between calling this function is not less than 0.5 seconds. } }

Result

Press button A of micro:bit or pull down the Arduino Pin A0, then HUSKYLENS will take a screenshot and save it in SD card. Take out the SD card and insert it into a computer, then you can view the screenshot taken by HUSKYLENS.

The image shown on the sucreen of HUSKYLENS

Read the image file(.bmp) on the SD card on a computer

HUSKYLENS supports taking multiple objects learned from the same algorithm as one data model. The SD card can be used to save the model. The model can be reloaded even if all the data from the current algorithm is deleted, allowing HUSKYLENS to automatically learn the data in the model. By saving the model, HUSKYLENS can be used for multiple scenes in one algorithm. For example, in the object classification algorithm, learn rock-paper-scissors as one model and garbage classification as one model. Then, through model switching, the required functions can be quickly realized to avoid repeating learning.

This function requires an SD card, which needs to be formatted as FAT32. All 7 algorithms, each of which can save 5 models, support SD card saving and loading models.

Here we take the object classification function as a demonstration. The usage in other algorithms are the same.

1. Learn new objects: Let HUSKYLENS learn several new objects. For example: in the object classification function, learn several animals with different ID numbers in turn.

2. Export model: long press "Function Button" to enter parameter settings interface of the secondary menu in the classification function, and then dial "Function Button" to the right until the option of "export to SD card" (that is, save the model to the SD card). Short press "Function Button", dial "Function Button", select anyone from 0 to 4(equivalent to select the save location, making it easy to distinguish the different models), then short press "Function Button" to save the model.

After the model is exported to the SD card, read the SD card with the computer, and you can see the model data file with suffix .conf in the "HUSKYLENS" folder. The file names saved by different algorithms are different. Shown as below:

Tip: According to the names of the files, we can know which algorithm function the exported model data file belongs to. The pictures learned in each model cannot be viewed.

3. Import model: When the model data file is already in the SD card, we can directly import it into HUSKYLENS. For example, in the object classification function, if the model data file of object classification is already in the SD card, then, just select "Import from SD Card" in parameter setting interface of secondary menu of object classification function, and select anyone from 0 to 4 to load the model into HUSKYLENS.

After importing the model, HUSKYLENS can realize recognition using the current model.

Tips: When importing models, only models with the same algorithm are supported.

In this way, micro:bit, Arduino, and other mainboards can be used to automatically trigger the saving or loading of model files. The following code block can be used to achieve this function.

Mind+ Block:

MakeCode Block:

Arduino function:

bool saveModelToSDCard(int fileNum)； bool loadModelFromSDCard(int fileNum)；

7.8.5 Make A Program to Trigger Learning Function

In addition to manually pressing the "learn button" to learn the target object, it can also be triggered programmatically. This function enables micro: Bit, Arduino, and other mainboards to automatically control the learning of HUSKYLENS.
All 7 algorithms of HUSKYLENS support this function.

Demonstration: Press button A on the mainboard of micro:bit or pull down the Arduino Pin A0 to let HUSKYLENS learn the object once. The object's ID is 1.

Mind+ Sample Program:

MakeCode Sample Program:

Arduino Sample Program:

#include "HUSKYLENS.h" HUSKYLENS huskylens; void setup() { Serial.begin(115200); pinMode(A0,INPUT_PULLUP); Wire.begin(); while (!huskylens.begin(Wire)) { Serial.println(F("Begin failed!")); delay(100); } } void loop() { if(digitalRead(A0) == 0) { while (!huskylens.writeLearn(1)) // bool writeLearn(int ID) { Serial.println(F("learn object ID1 failed!")); delay(100); } Serial.println(F("learn object ID1 success")); } }

Result

In object classification mode, aim HUSKYLENS at the following three images in turn. Press button A of micro:bit or pull down the Arduino Pin A0, then HUSKYLENS will learn these three images as objects:ID1 in turn. When HUSKYLENS recognizes any of these three images again, it displays object:ID1 on the screen, indicating that the three workers are wearing safety hats.

Here you can customize the name of ID1, such as safe:ID1; You can also customize the text on the screen, overlaying relevant information to indicate that the status is with safety hat. With the information, the recognition results are easy to understand.

8. Arduino Tutorial

Please download and install the HUSKYLENS Library first.

8.1 Install the Library

Unzip the file, then copy the folder to the "libraries" folder of the Arduino IDE. Then check whether the folder name is "HUSKYLENS". If not, please change it as "HUSKYLENS". Please note that the library file name must be HUSKYLENS.

All .h files and .cpp files must in the root directory of the "HUSKYELSN" folder.

8.2 Project 1: Read Position Data

In this project, HuskyLens will be connected to Arduino mainboard. And Arduino Uno will read position data of the object from HuskyLens. Then the serial port monitor will print the data. So that, you can read the position of the object in real time.

Requirements

UART Mode(SoftwareSerial)

Connection Diagram

HuskyLens Protocol Setting

You need to set the protocol type of HuskyLens. The protocol should be 'Serial 9600'. Of course, your can adopt the Auto Detect protocol, which is easy-to-use and convenient.

Sample Code

#include "HUSKYLENS.h" #include "SoftwareSerial.h" HUSKYLENS huskylens; SoftwareSerial mySerial(10, 11); // RX, TX //HUSKYLENS green line >> Pin 10; blue line >> Pin 11 void printResult(HUSKYLENSResult result); void setup() { Serial.begin(115200); mySerial.begin(9600); while (!huskylens.begin(mySerial)) { Serial.println(F("Begin failed!")); Serial.println(F("1.Please recheck the \"Protocol Type\" in HUSKYLENS (General Settings>>Protocol Type>>Serial 9600)")); Serial.println(F("2.Please recheck the connection.")); delay(100); } } void loop() { if (!huskylens.request()) Serial.println(F("Fail to request data from HUSKYLENS, recheck the connection!")); else if(!huskylens.isLearned()) Serial.println(F("Nothing learned, press learn button on HUSKYLENS to learn one!")); else if(!huskylens.available()) Serial.println(F("No block or arrow appears on the screen!")); else { Serial.println(F("###########")); while (huskylens.available()) { HUSKYLENSResult result = huskylens.read(); printResult(result); } } } void printResult(HUSKYLENSResult result){ if (result.command == COMMAND_RETURN_BLOCK){ Serial.println(String()+F("Block:xCenter=")+result.xCenter+F(",yCenter=")+result.yCenter+F(",width=")+result.width+F(",height=")+result.height+F(",ID=")+result.ID); } else if (result.command == COMMAND_RETURN_ARROW){ Serial.println(String()+F("Arrow:xOrigin=")+result.xOrigin+F(",yOrigin=")+result.yOrigin+F(",xTarget=")+result.xTarget+F(",yTarget=")+result.yTarget+F(",ID=")+result.ID); } else{ Serial.println("Object unknown!"); } }

Operations and Expected Results

1. Upload the above codes to your Arduino board.

2. Let your HuskyLens learn a new thing first. You can refer to the previous chapters of this tutorial.

3. Open the serial monitor of Arduino IDE, then you will get the position data of the object.

If HuskyLens is in the face recognition, object tracking, object recognition, color recognition, tag recognition mode, you will get the results like follows:

If HuskyLens is in the line tracking mode, you will get the results like follows:

I2C Mode

Connection Diagram

HuskyLens Protocol Setting

You need to set the protocol type of HuskyLens. The protocol should be 'I2C'. Of course, your can adopt the auto detect protocol, which is easy-to-use and convenient.

Sample Code

#include "HUSKYLENS.h" #include "SoftwareSerial.h" HUSKYLENS huskylens; //HUSKYLENS green line >> SDA; blue line >> SCL void printResult(HUSKYLENSResult result); void setup() { Serial.begin(115200); Wire.begin(); while (!huskylens.begin(Wire)) { Serial.println(F("Begin failed!")); Serial.println(F("1.Please recheck the \"Protocol Type\" in HUSKYLENS (General Settings>>Protocol Type>>I2C)")); Serial.println(F("2.Please recheck the connection.")); delay(100); } } void loop() { if (!huskylens.request()) Serial.println(F("Fail to request data from HUSKYLENS, recheck the connection!")); else if(!huskylens.isLearned()) Serial.println(F("Nothing learned, press learn button on HUSKYLENS to learn one!")); else if(!huskylens.available()) Serial.println(F("No block or arrow appears on the screen!")); else { Serial.println(F("###########")); while (huskylens.available()) { HUSKYLENSResult result = huskylens.read(); printResult(result); } } } void printResult(HUSKYLENSResult result){ if (result.command == COMMAND_RETURN_BLOCK){ Serial.println(String()+F("Block:xCenter=")+result.xCenter+F(",yCenter=")+result.yCenter+F(",width=")+result.width+F(",height=")+result.height+F(",ID=")+result.ID); } else if (result.command == COMMAND_RETURN_ARROW){ Serial.println(String()+F("Arrow:xOrigin=")+result.xOrigin+F(",yOrigin=")+result.yOrigin+F(",xTarget=")+result.xTarget+F(",yTarget=")+result.yTarget+F(",ID=")+result.ID); } else{ Serial.println("Object unknown!"); } }

Operations and Expected Results

1. Upload the above codes to your Arduino board.

2. Let your HuskyLens learn a new thing first. You can refer to the previous chapters of this tutorial.

3. Open the serial monitor of Arduino IDE, then you will get the position data of the object, same as the results in UART mode. Please refer to the previous chapter, which will not be repeated here.

8.3 Project 2: DIY Line Tracking Robot

In this part, we will use the Devastator Tank Mobile Robot, HuskyLens and Romeo board to make a line tracking robot.

Please refer this post to get the demonstration.

8.4 Arduino API Introduction

Please click here to view the API introduction documents.

9. micro:bit Tutorial

In this chapter, we will use micro:bit board to read data from the HuskyLens. The communication protocol is I2C. We adopt Mind+ and MakeCode, then combine with several project cases to demonstrate the usage.

Now we adopt Mind + for demonstration first. Later we adopt MakeCode to demonstrate.

9.1 Mind+ Introduction

Mind+ is a Scratch 3.0-based programming tool, which allows you to build a program by dragging and snapping coding blocks. With tons of tutorials, sample projects and a large community, it is one of the best tools for you to learn programing from absolutely zero!

Mind+ supports a wide range of hardware including Arduino, micro:bit or even a series of ESP32-based educational microcontrollers.

Please view Mind+ official site http://mindplus.cc to download the latest Mind+.

9.2 Load HuskyLens Extension

1. Click the Extensions button in the lower left corner to view the extensions window.

2. After selecting the board, the corresponding extension labels become selectable. Then click Sensor label, find HuskyLens. Click it to load.

You can enter the sensor's name in the search bar in upper right corner when there are many sensors listed in the menu.

3. After selecting the board and extensions, click Back button in the upper left corner to return to the programming window.

9.3 Mind+ Project 1: Face Recognition

This chapter demonstrates how to connect HuskyLens to the micro: bit board, then the micro: bit board reads the face recognition results from HuskyLens. If HuskyLens recognizes you (the learned face), the dot-matrix screen of the micro: bit displays a smiling face, otherwise it displays a crying face.

The communication protocol between HuskyLens and micro: bit is I2C.

Requirements

Connection Diagram

The following picture is only for reference when wiring. The R and T pins of HuskyLens (their functions are SCL and SDA here) are connected to the SCL (P19) and SDA (P20) pins of the micro: bit respectively. The communication protocol between HuskyLens and micro: bit is I2C.

A micro: bit expansion board is recommended for simplify wiring.

Tips: HuskyLens consumes heavy current, up to 3.3V 320mA or more. The mciro: bit board is not enough to supply power. Therefore, external power supply is required. You can connect the external power supply to the external power connector of the micro: bit expansion board or the USB connector of HuskyLens.

HuskyLens Protocol Setting

You need to set the protocol type of HuskyLens. The protocol should be I2C. Of course, your can adopt the auto detect protocol, which is easy-to-use and convenient.

Sample Code

Drag and snap the coding blocks to program, and make a simple face recognition projects. The sample code is shown below.

Operations and Expected Results

Click the Connect Device button, then select the COM port corresponding to the microbit.

If no COM port is found or you use mcirobit for the first time, please click the Install Serialport Driver button to install the driver with one click.

1. Click the Upload button to upload the sample code to your micro:bit board.

2. Let your HuskyLens learn your face first. You can refer to the chapter 7.1 of this tutorial.

3. When HuskyLens recognizes your face, the dot-matrix screen on the micro: bit board will show a smiling face. If it were not your face, or no face appeared, it would display a crying face.

9.4 Coding Block Introduction

Please download Description of HuskyLens Blocks in Mind+.pdf document.

Below, we adopt MakeCode for demonstration below.

9.5 MakeCode Introduction

Microsoft MakeCode is a free, open source platform for creating engaging computer science learning experiences that support a progression path into real-world programming. Click here to view the MakeCode for micro:bit.

9.6 Load HuskyLens Extension

Create a new project in MakeCode web version, and then click the "More..." button (gear icon) at the top right and select "Extensions" from its drop-down menu to open the extension page.

Enter huskylens in the search bar, then click the search button (the magnifying glass button on the right of the search bar) , you will see the HuskyLens extensions. Then click it to load the HuskyLens extension into the MakeCode.

In the programming page, you can see the Huskylens module.

9.7 Project 1: Face Recognition

This chapter demonstrates how to connect HuskyLens to the micro: bit board, then the micro: bit board reads the face recognition results from HuskyLens. If HuskyLens recognizes you (the learned face), the dot-matrix screen of the micro: bit displays a smiling face, otherwise it displays a crying face.

The communication protocol between HuskyLens and micro: bit is I2C.

Requirements

Connection Diagram

The following picture is only for reference when wiring. The R and T pins of HuskyLens (their functions are SCL and SDA here) are connected to the SCL (P19) and SDA (P20) pins of the micro: bit respectively. The communication protocol between HuskyLens and micro: bit is I2C.

A micro: bit expansion board is recommended for simplify wiring.

Tips: HuskyLens consumes heavy current, up to 3.3V 320mA or more. The mciro: bit board is not enough to supply power. Therefore, external power supply is required. You can connect the external power supply to the external power connector of the micro: bit expansion board, or the HuskyLens USB connector.

HuskyLens Protocol Setting

You need to set the protocol type of HuskyLens. The protocol should be I2C. Of course, your can adopt the auto detect protocol, which is easy-to-use and convenient.

Sample Code

Operations and Expected Results

1. Upload the above codes to the micro: bit board.

2. Refer to the previous chapter which explaining the face recognition function(chapter 7.1), let your HuskyLens learn a face, such as your face.

3. When HuskyLens recognizes your face, the dot-matrix screen on the micro: bit board will show a smiling face. If it were not your face, or no face appeared, it would display a crying face.

9.8 Coding Block Introduction

Please refer Description of HuskyLens Blocks in Mind+.pdf document. The name of the coding blocks are almost the same.

10. FAQ

Q. When I upload the firmware by the k-flash, but I get the "end of central directory record could not be found" error message. How can I fix this?

A. The firmware you downloaded is not correct, that is, The file is incomplete and wrong. (e.g. The correct firmware is up to 9MB, but the firmware you download is only 66KB.) It may caused by the unstable network or other matters. Please download it from the github again. https://github.com/HuskyLens/HUSKYLENSUploader

For any questions, advice or cool ideas to share, please visit the DFRobot Forum.

11. More Documents

Get HUSKYLENS from DFRobot Store or DFRobot Distributor.

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Gravity: HUSKYLENS AI Machine Vision Sensor - DFRobot Wiki

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HuskyLens is an easy-to-use AI machine vision sensor with 7 built-in functions: face recognition, object tracking, object recognition, line tracking, color recognition, tag recognition and object classification.

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Programmation Huskylens et Maqueen+ (Gotronic)

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Programmation Huskylens et Maqueen+ (Gotronic)

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Aujourd'hui, nous allons programmer un robot Maqueen Plu s

avec un Module AI HusKyLens Gravity SEN0305 et une carte micro : bit.

Nous avons assemblé le Maqueen et le HusKylens dans ce pack.

Le Maqueen Plus de DFRobot est un robot pilotable grâce à une carte micro:bit (non incluse). Ce châssis est doté de plusieurs modules complémentaires:

2 x encodeurs pour motoréducteurs

6 x modules suiveurs de lignes

1 x capteur US URM10

1 x récepteur IR pour le contrôle via une télécommande IR (non incluse, voir IRC01)

Ce châssis comporte également 2 LEDs RGB (6 couleurs), un buzzer et plusieurs E/S déportées de la carte micro:bit (3 Vcc, I2C, 3 sorties servos)
Certains de ces E/S sont partagées avec plusieurs modules de la carte.

Ce robot est également pilotable via une seconde carte micro:bit (non incluse) via une liaison Bluetooth. Cette seconde carte micro:bit peut notamment être utilisée avec la manette micro:Gamepad de DFRobot.

Le Module AI HuskyLens Gravity SEN0305 est un module doté d'un écran et d'une caméra qui nous permettrons d'effectuer plusieurs applications, qui sont déjà intégrées au module tel que :

Nous utiliseront le brochage en I2C du module pour nos applications.

Le châssis du Maqueen plus est entièrement compatible avec la caméra HuskyLens AI permettant l'ajout de la reconnaissance visuelle intelligente à vos projets.

C'est pour cela que nous avons combinés les deux, on ce retrouve donc avec un robot qui a une camera à la place du capteur à ultrasons. Avec cela on peut utiliser toutes les fonctions du Maqueen et y rajouter certains aspects du module HusKylens.

On vous propose 4 projet pour contrôler le robot :

- Suiveur d'objet.

- Suiveur de ligne + ordre donné par QR code.

- Route à suivre en fonction des QR code visualisés.

- Trieur d'objet via QR code.

Le robot est à monter sois même. Tout d'abord, installez l'accu (attention au sens), puis vissez les 3 entretoises derrière l'accu pour y installer le support métallique, ensuite insérez les roues, puis insérez la carte micro:bit dans son connecteur à l'avant du châssis, pour finir vissez le module HusKyLens sur le support métallique à la place du capteur à ultrasons.

Pour contrôler le robot, nous allons devoir programmer la carte micro:bit. Si vous êtes débutant avec micro:bit, référez-vous à cet

Par simplicité, nous utiliserons la programmation en blocs. Rendez-vous sur le site . Lorsque vous serez sur l'éditeur, cliquez sur En haut de la page se trouvent deux boutons : Blocs et JavaScript. Assurez-vous d'être dans Blocs. À gauche, cliquez sur Nouveau projet. Avancé puis sur Extensions. Dans la barre Rechercher ou entrer l'URL du projet, copiez-collez les liens suivant :

Passons à la programmation.

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Contrôle d'un robot Maqueen plus HusKyLens - Le Blog Gotronic

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Quelques conseils pour participer à la Robocup Junior.

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ROBOCUP JUNIOR Ile de France 2022 CONSEILS ET RESSOURCES

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Les robots sont partout - Science & Vie Junior Hors-Série N°145 - Bienvenue dans un monde de robots