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Coding Journey's Projects

d2go icon d2go

D2Go is a toolkit for efficient deep learning

detectron2 icon detectron2

Detectron2 is FAIR's next-generation platform for object detection and segmentation.

fastdeploy icon fastdeploy

⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.

imgaug icon imgaug

Image augmentation for machine learning experiments.

krypton icon krypton

Krypton WinForms components for .NET

labelme icon labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

nanodet icon nanodet

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

ncnn icon ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

onnx_tflite_yolov3 icon onnx_tflite_yolov3

A Conversion tool to convert YOLO v3 Darknet weights to TF Lite model (YOLO v3 PyTorch > ONNX > TensorFlow > TF Lite), and to TensorRT (YOLO v3 Pytorch > ONNX > TensorRT).

paddledetection icon paddledetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

paddleocr icon paddleocr

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

pelee icon pelee

Pelee: A Real-Time Object Detection System on Mobile Devices

tensorflow-lite-yolov3 icon tensorflow-lite-yolov3

YOLOv3: convert .weights to .tflite format for tensorflow lite. Convert .weights to .pb format for tensorflow serving

tensorflow-yolov4-tflite icon tensorflow-yolov4-tflite

YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite

ultralytics icon ultralytics

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

yolo-fastest icon yolo-fastest

:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+

yolov3 icon yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

yolov5 icon yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

yolov7 icon yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

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