tensorflow-lite-YOLOv3
tensorflow-yolov4-tflite
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tensorflow-lite-YOLOv3 | tensorflow-yolov4-tflite | |
---|---|---|
2 | 4 | |
107 | 2,220 | |
- | - | |
0.0 | 0.0 | |
7 months ago | 11 months ago | |
Python | Python | |
- | MIT License |
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tensorflow-lite-YOLOv3
tensorflow-yolov4-tflite
- Object tracking on Android
-
Tensorflow Yolo Implementation
Hello all, I've been desperate for help in the tensorflow yolo objection detection framework. Basically, in https://github.com/hunglc007/tensorflow-yolov4-tflite 's implementation, there is problem whereby with GPU, it only detects the first frame in the whole video while CPU works fine but absolutely slow. There are issues opened at https://github.com/hunglc007/tensorflow-yolov4-tflite/issues/282 but no proper solution is found. I've also opened a question stackoverflow: https://stackoverflow.com/questions/68333281/tensorflow-yolov4-detect-video
- “ValueError: cannot reshape array of size 278540 into shape (256,128,3,3)” Conversion YOLOv3 .weights to .pb
What are some alternatives?
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
faiss-server - faiss serving :)
edge-tpu-tiny-yolo - Run Tiny YOLO-v3 on Google's Edge TPU USB Accelerator.
pdf2image - A python module that wraps the pdftoppm utility to convert PDF to PIL Image object
Swin-Transformer-Tensorflow - Unofficial implementation of "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" (https://arxiv.org/abs/2103.14030)
yolov3-tf2 - YoloV3 Implemented in Tensorflow 2.0
yolo-tensorrt - TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.
tflite2tensorflow - Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.
tensorrtx - Implementation of popular deep learning networks with TensorRT network definition API