Update README.md

README.md

@@ -5,10 +5,16 @@ tags:
 - computer vision
 - darknet
 - yolo
+- tensorflow
 
 datasets:
 - coco
 - imagenette
+
+license: mit
+
+thumbnail: https://github.com/hunglc007/tensorflow-yolov4-tflite
+ 
 ---
 
 # TensorFlow-yolov4-tflite
@@ -27,7 +33,6 @@ This yolov4 library uses Tensorflow 2.0 and is available on. this [Github](https
 
 ### What can you use yolov4-tflite for?
 
-
 ```bash
 # Convert darknet weights to tensorflow
 ## yolov4
@@ -85,7 +90,7 @@ python save_model.py --weights ./data/yolov4.weights --output ./checkpoints/yolo
 python convert_trt.py --weights ./checkpoints/yolov4.tf --quantize_mode float16 --output ./checkpoints/yolov4-trt-fp16-416
 ```
 
-### Evaluate on COCO 2017 Dataset
+### Evaluated on COCO 2017 Dataset
 ```bash
 # run script in /script/get_coco_dataset_2017.sh to download COCO 2017 Dataset
 # preprocess coco dataset
@@ -157,13 +162,6 @@ python benchmarks.py --size 416 --model yolov4 --weights ./data/yolov4.weights
 | YoloV3 FPS  |         |         |         |
 | YoloV4 FPS  |         |         |         |
 
-### Traning your own model
-```bash
-# Prepare your dataset
-# If you want to train from scratch:
-In config.py set FISRT_STAGE_EPOCHS=0 
-# Run script:
-python train.py
 
 # Transfer learning: 
 python train.py --weights ./data/yolov4.weights