hunglc007/tensorflow-yolov4-tflite

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2254 stars · 1220 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A TensorFlow 2.x implementation of YOLOv4, YOLOv4-tiny, YOLOv3, and YOLOv3-tiny object detection models, with scripts that convert original Darknet .weights into TensorFlow, TensorFlow Lite, and TensorRT formats. It includes detection and video demos, training, mAP evaluation, and float16/int8 quantization for deployment on desktop, NVIDIA GPUs, and Android.

Use cases

• convert darknet yolov4 weights to tensorflow 2
• run yolov4 object detection on images or video in python
• convert yolo model to tflite for android deployment
• quantize yolov4 to int8 or float16 tflite
• convert yolo weights to tensorrt for faster gpu inference
• train yolov4 on a custom dataset in tensorflow
• benchmark yolov4-tiny for real-time detection

When to choose

• You need official Darknet YOLOv4/v3 weights running inside a TensorFlow 2.x pipeline
• You are deploying to mobile or edge devices and need TFLite conversion with quantization
• You want TensorRT-optimized YOLO inference on NVIDIA GPUs
• You want reference code for training or evaluating YOLO models in TensorFlow rather than Darknet

When to avoid

• You want newer YOLO generations (YOLOv7/v8+) or prefer the PyTorch ecosystem
• You need production-grade int8 quantized YOLOv4/v4-tiny, which the README acknowledges has known issues
• Your stack requires a modern TensorFlow version, since the project targets TF 2.3-era APIs
• You need a maintained turnkey detection service rather than scripts and model code

Facets

library · maturity maintenance

deep-learning machine-learning computer-vision image-processing gpu-computing computer-vision deep-learning machine-learning mobile-development python cross-platform yolov4 yolov3 object-detection tensorflow2 tflite tensorrt model-conversion darknet-weights int8-quantization real-time-detection android gpu

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