#jupyter_notebook #coreml #ios #object_detection #onnx #pytorch #tflite #yolov3 #yolov4 #yolov5

https://github.com/ultralytics/yolov5

#javascript #ai #caffe #caffe2 #coreml #darknet #deep_learning #deeplearning #keras #machine_learning #machinelearning #ml #mxnet #neural_network #onnx #paddle #pytorch #tensorflow #tensorflow_lite #torch #visualizer

https://github.com/lutzroeder/netron

#python #ai #artificial_intelligence #computer_vision #coreml #deep_learning #high_resolution #machine_learning #matting #onnx #pytorch #real_time #tensorflow #tfjs #video_matting

https://github.com/PeterL1n/RobustVideoMatting

#python #caffe #computer_vision #coreml #edgetpu #keras #mediapipe #model #model_zoo #models #onnx #openvino #pretrained_models #pytorch #tensorflow #tensorflow_lite #tensorflowjs #tf_trt #tfjs #tflite #tflite_models

https://github.com/PINTO0309/PINTO_model_zoo

#swift #arkit #article #awesome_list #clean_code #combine #coreml #coreml_framework #curated_list #design_patterns #ios #learning #metal #mvvm #scenekit #spritekit #swiftui #tutorial #uikit #xcode

https://github.com/eleev/ios-learning-materials

#python #coreml #deep_learning #ios #machine_learning #ml #object_detection #onnx #pytorch #tflite #ultralytics #yolo #yolov3 #yolov5

YOLOv5 is a powerful and easy-to-use AI model for object detection, image segmentation, and classification. It is designed to be fast, accurate, and simple to implement. Here are the key benefits YOLOv5 is straightforward to set up and use, with detailed documentation and tutorials available.
- **Performance** You can use YOLOv5 for object detection, image segmentation, and classification tasks.
- **Community Support** You can run YOLOv5 in various environments such as Google Colab, Paperspace, Kaggle, and Docker.

Overall, YOLOv5 simplifies the process of integrating advanced AI capabilities into your projects.

https://github.com/ultralytics/yolov5

#python #chinese #clip #computer_vision #contrastive_loss #coreml_models #deep_learning #image_text_retrieval #multi_modal #multi_modal_learning #nlp #pretrained_models #pytorch #transformers #vision_and_language_pre_training #vision_language

This project is about a Chinese version of the CLIP (Contrastive Language-Image Pretraining) model, trained on a large dataset of Chinese text and images. Here’s what you need to know This model helps you quickly perform tasks like calculating text and image features, cross-modal retrieval (finding images based on text or vice versa), and zero-shot image classification (classifying images without any labeled examples).
- **Ease of Use** The model has been tested on various datasets and shows strong performance in zero-shot image classification and cross-modal retrieval tasks.
- **Resources**: The project includes pre-trained models, training and testing codes, and detailed tutorials on how to use the model for different tasks.

Overall, this project makes it easy to work with Chinese text and images using advanced AI techniques, saving you time and effort.

https://github.com/OFA-Sys/Chinese-CLIP