Update README.md

README.md

@@ -25,70 +25,7 @@ This YOLOv4 library, inspired by previous YOLOv3 implementations here:
   * [Yolov3 tensorflow](https://github.com/YunYang1994/tensorflow-yolov3)
   * [Yolov3 tf2](https://github.com/zzh8829/yolov3-tf2)uses Tensorflow 2.0 and is available on this [Github](https://github.com/hunglc007/tensorflow-yolov4-tflite). 
 
-
-### Prerequisites
-* Tensorflow 2.3.0rc0
-
-### How to use yolov4-tflite
-
-```bash
-# Convert darknet weights to tensorflow
-## yolov4
-python save_model.py --weights ./data/yolov4.weights --output ./checkpoints/yolov4-416 --input_size 416 --model yolov4 
-
-## yolov4-tiny
-python save_model.py --weights ./data/yolov4-tiny.weights --output ./checkpoints/yolov4-tiny-416 --input_size 416 --model yolov4 --tiny
-
-# Run demo tensorflow
-python detect.py --weights ./checkpoints/yolov4-416 --size 416 --model yolov4 --image ./data/kite.jpg
-
-python detect.py --weights ./checkpoints/yolov4-tiny-416 --size 416 --model yolov4 --image ./data/kite.jpg --tiny
-
-```
-If you want to run yolov3 or yolov3-tiny change ``--model yolov3`` in command
-
-#### Output
-
-##### Yolov4 original weight
-<p align="center"><img src="result.png" width="640"\></p>
-
-##### Yolov4 tflite int8
-<p align="center"><img src="result-int8.png" width="640"\></p>
-
-### Convert to tflite
-
-```bash
-# Save tf model for tflite converting
-python save_model.py --weights ./data/yolov4.weights --output ./checkpoints/yolov4-416 --input_size 416 --model yolov4 --framework tflite
-
-# yolov4
-python convert_tflite.py --weights ./checkpoints/yolov4-416 --output ./checkpoints/yolov4-416.tflite
-
-# yolov4 quantize float16
-python convert_tflite.py --weights ./checkpoints/yolov4-416 --output ./checkpoints/yolov4-416-fp16.tflite --quantize_mode float16
-
-# yolov4 quantize int8
-python convert_tflite.py --weights ./checkpoints/yolov4-416 --output ./checkpoints/yolov4-416-int8.tflite --quantize_mode int8 --dataset ./coco_dataset/coco/val207.txt
-
-# Run demo tflite model
-python detect.py --weights ./checkpoints/yolov4-416.tflite --size 416 --model yolov4 --image ./data/kite.jpg --framework tflite
-```
-Yolov4 and Yolov4-tiny int8 quantization have some issues. I will try to fix that. You can try Yolov3 and Yolov3-tiny int8 quantization 
-### Convert to TensorRT
-```bash# yolov3
-python save_model.py --weights ./data/yolov3.weights --output ./checkpoints/yolov3.tf --input_size 416 --model yolov3
-python convert_trt.py --weights ./checkpoints/yolov3.tf --quantize_mode float16 --output ./checkpoints/yolov3-trt-fp16-416
-
-# yolov3-tiny
-python save_model.py --weights ./data/yolov3-tiny.weights --output ./checkpoints/yolov3-tiny.tf --input_size 416 --tiny
-python convert_trt.py --weights ./checkpoints/yolov3-tiny.tf --quantize_mode float16 --output ./checkpoints/yolov3-tiny-trt-fp16-416
-
-# yolov4
-python save_model.py --weights ./data/yolov4.weights --output ./checkpoints/yolov4.tf --input_size 416 --model yolov4
-python convert_trt.py --weights ./checkpoints/yolov4.tf --quantize_mode float16 --output ./checkpoints/yolov4-trt-fp16-416
-```
-
-### Evaluated on COCO 2017 Dataset
+### Evaluate on COCO 2017 Dataset
 ```bash
 # run script in /script/get_coco_dataset_2017.sh to download COCO 2017 Dataset
 # preprocess coco dataset