Remove scripts using darknet pretrained models

lmnet/README.md

@@ -15,7 +15,6 @@ This project is developed as one part of Blueoil project -- the deep learning mo
 
 * Utils
   * `measure_latency.py`: entry point script for measuring inference latency.
-  * `convert_weight_from_darknet.py`: entry point script for convert weight format form darknet framework.
 
 - - -
 
@@ -343,34 +342,6 @@ e.g.
 `PYTHONPATH=. python executor/predict.py -in ./dataset/images -o ./outputs -i lmnet_cifar10`
 
 
-# Convert weight from darknet
-Weight converter form darknet framework to tensorflow checkpoints file.
-You can convert [Yolov2](https://pjreddie.com/darknet/yolov2/) and [Darknet19](https://pjreddie.com/darknet/imagenet/#darknet19_448) network weights.
-
-Please download darknet weights at `inputs` dir.
-```
-cd inputs
-wget http://pjreddie.com/media/files/darknet19_448.weights
-wget https://pjreddie.com/media/files/yolo-voc.weights
-```
-
-After execute `convert_weight_from_darknet.py`, You can get checkpoints file on
-* darknet19: `${OUTPUT_DIR}/convert_weight_from_darknet/darknet19/checkpoints/save.ckpt`
-* yolov2: `${OUTPUT_DIR}/convert_weight_from_darknet/yolo_v2/checkpoints/save.ckpt`
-
-```
-# PYTHONPATH=. python executor/convert_weight_from_darknet.py -h
-Usage: convert_weight_from_darknet.py [OPTIONS]
-
-Options:
-  -m, --model [yolov2|darknet19]  yolo2 or darknet19  [required]
-  -h, --help                      Show this message and exit.
-```
-
-e.g.
-`PYTHONPATH=. python executor/convert_weight_from_darknet.py -m yolov2`
-
-
 # Profiling model
 Profiling a trained model.
 

lmnet/tests/test_configs.py

@@ -34,15 +34,6 @@ def test_core_configs():
         check_config(config, "inference")
 
 
-def test_convert_weight_from_darknet_configs():
-    """Test that all config files in `configs/convert_weight_from_darknet` dir include requirement keys."""
-    dir_path = os.path.join("configs", "convert_weight_from_darknet")
-
-    for config_file in glob.glob(os.path.join(dir_path, "**", "*.py"), recursive=True):
-        config = _load_py(config_file)
-        check_config(config, "inference")
-
-
 def test_example_config():
     """Test that example config python file include requirement keys."""
 
@@ -111,7 +102,6 @@ def test_example_object_detection_config_yaml():
 
 if __name__ == '__main__':
     test_core_configs()
-    test_convert_weight_from_darknet_configs()
     test_example_config()
     test_example_classification_config_yaml()
     test_example_object_detection_config_yaml()