Merge pull request #95 from Satgoy152:adding-doc

Improved help messages for demo programs (#95)
- Added Demo Documentation
- Updated help messages
- Changed exception link

README.md

@@ -6,23 +6,27 @@ MobileNetV2: Inverted Residuals and Linear Bottlenecks
 
 Results of accuracy evaluation with [tools/eval](../../tools/eval).
 
-| Models | Top-1 Accuracy | Top-5 Accuracy |
-| ------ | -------------- | -------------- |
-| MobileNet V1 | 67.64 | 87.97 |
-| MobileNet V1 quant | 55.53 | 78.74 |
-| MobileNet V2 | 69.44 | 89.23 |
-| MobileNet V2 quant | 68.37 | 88.56 |
+| Models             | Top-1 Accuracy | Top-5 Accuracy |
+| ------------------ | -------------- | -------------- |
+| MobileNet V1       | 67.64          | 87.97          |
+| MobileNet V1 quant | 55.53          | 78.74          |
+| MobileNet V2       | 69.44          | 89.23          |
+| MobileNet V2 quant | 68.37          | 88.56          |
 
 \*: 'quant' stands for 'quantized'.
 
 ## Demo
 
 Run the following command to try the demo:
+
 ```shell
 # MobileNet V1
 python demo.py --input /path/to/image
 # MobileNet V2
 python demo.py --input /path/to/image --model v2
+
+# get help regarding various parameters
+python demo.py --help
 ```
 
 ## License
@@ -35,4 +39,3 @@ All files in this directory are licensed under [Apache 2.0 License](./LICENSE).
 - MobileNet V2: https://arxiv.org/abs/1801.04381
 - MobileNet V1 weight and scripts for training: https://github.com/wjc852456/pytorch-mobilenet-v1
 - MobileNet V2 weight: https://github.com/onnx/models/tree/main/vision/classification/mobilenet
-

demo.py

@@ -24,14 +24,14 @@ try:
     help_msg_backends += "; {:d}: TIMVX"
     help_msg_targets += "; {:d}: NPU"
 except:
-    print('This version of OpenCV does not support TIM-VX and NPU. Visit https://gist.github.com/fengyuentau/5a7a5ba36328f2b763aea026c43fa45f for more information.')
+    print('This version of OpenCV does not support TIM-VX and NPU. Visit https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU for more information.')
 
 parser = argparse.ArgumentParser(description='Demo for MobileNet V1 & V2.')
-parser.add_argument('--input', '-i', type=str, help='Path to the input image.')
-parser.add_argument('--model', '-m', type=str, choices=['v1', 'v2', 'v1-q', 'v2-q'], default='v1', help='Which model to use, either v1 or v2.')
+parser.add_argument('--input', '-i', type=str, help='Usage: Set input path to a certain image, omit if using camera.')
+parser.add_argument('--model', '-m', type=str, choices=['v1', 'v2', 'v1-q', 'v2-q'], default='v1', help='Usage: Set model type, defaults to image_classification_mobilenetv1_2022apr.onnx (v1).')
 parser.add_argument('--backend', '-b', type=int, default=backends[0], help=help_msg_backends.format(*backends))
 parser.add_argument('--target', '-t', type=int, default=targets[0], help=help_msg_targets.format(*targets))
-parser.add_argument('--label', '-l', type=str, default='./imagenet_labels.txt', help='Path to the dataset labels.')
+parser.add_argument('--label', '-l', type=str, default='./imagenet_labels.txt', help='Usage: Set path to the different labels that will be used during the detection. Default list found in imagenet_labels.txt')
 args = parser.parse_args()
 
 if __name__ == '__main__':