update and modify documentation (#161)

README.md

@@ -4,11 +4,11 @@ This model detects palm bounding boxes and palm landmarks, and is converted from
 
 - TFLite model to ONNX: https://github.com/onnx/tensorflow-onnx
 - simplified by [onnx-simplifier](https://github.com/daquexian/onnx-simplifier)
-- SSD Anchors are generated from [GenMediaPipePalmDectionSSDAnchors](https://github.com/VimalMollyn/GenMediaPipePalmDectionSSDAnchors)
 
+SSD Anchors are generated from [GenMediaPipePalmDectionSSDAnchors](https://github.com/VimalMollyn/GenMediaPipePalmDectionSSDAnchors)
 
 **Note**:
-- Visit https://google.github.io/mediapipe/solutions/models.html#hands for models of larger scale.
+- Visit https://github.com/google/mediapipe/blob/master/docs/solutions/models.md#hands for models of larger scale.
 
 ## Demo
 
@@ -18,7 +18,7 @@ Run the following commands to try the demo:
 # detect on camera input
 python demo.py
 # detect on an image
-python demo.py -i /path/to/image
+python demo.py -i /path/to/image -v
 
 # get help regarding various parameters
 python demo.py --help
@@ -34,6 +34,7 @@ All files in this directory are licensed under [Apache 2.0 License](./LICENSE).
 
 ## Reference
 
-- MediaPipe Handpose: https://github.com/tensorflow/tfjs-models/tree/master/handpose
-- MediaPipe hands model and model card: https://google.github.io/mediapipe/solutions/models.html#hands
+- MediaPipe Handpose: https://developers.google.com/mediapipe/solutions/vision/hand_landmarker
+- MediaPipe hands model and model card: https://github.com/google/mediapipe/blob/master/docs/solutions/models.md#hands
+- Handpose TFJS:https://github.com/tensorflow/tfjs-models/tree/master/handpose
 - Int8 model quantized with rgb evaluation set of FreiHAND: https://lmb.informatik.uni-freiburg.de/resources/datasets/FreihandDataset.en.html