tensorflow-yolov4-tflite
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YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
Hi @hunglc007 first thanks for all the work you've done. I have followed you tutorial on how to create a `yolov4-int8.tflite`. Then I got it successfully converted to `yolov4-int8_edgetpu.tflite` using...
Hi everyone, I have been working to deploy my YOLOv4 model to Flask recently. When I finished the deployment, I checked the performance of detection between the tf-yolov4 model and...
Hi all How to convert yolov4 weights developed using tensorflor1.15 in saved_model.pb file. Using this conversion mechanism, conversion is done but wont to cause issues since the existing implementation uses...
`Cannot copy between a TensorFlowLite tensor with shape [1, 10647, 4] and a Java object with shape [1, 52, 52, 3, 85]`
System information - windows 10 - python 3.6 - tensorflow 2.3.0 When I try to convert my own trained yolov3-tiny model to tflite with the following command: _python convert_tflite.py --weights...
Hello. I ran the command to change darknet weights to tensorflow weights in jetson nano, but it doesn't work as below. I've been facing a problem for a few days...
I would like to see the results by putting the yolov5 model in Android. So, after converting .pt to .tflite, I put it in the TF_OD_API_MODEL_FILE path, but I get...
I used the default hyper-parameters and trained the model on a single Nvidia Titan Xp. And the training logs show that the loss didn't converge. It apparently leaded to a...
@hunglc007 Hi, Why do you get only `61.96%` AP50 for YOLOv4-512x512 https://github.com/hunglc007/tensorflow-yolov4-tflite#map50-on-coco-2017-dataset instead of `64.9%` AP50 that I can get by using Darknet? https://github.com/AlexeyAB/darknet/wiki/How-to-evaluate-accuracy-and-speed-of-YOLOv4 Did you use https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v3_optimal/yolov4.weights for evaluation...
I have trained YOLOv4 from the darknet of AlexeyAB repository with my custom dataset after that i used the save_model.py to convert weight to tensorflow but the prediction is different...