Add back example output images as lfs tracked files (#166)
Browse files* lfs track images now
* add back example images
* modify paths
* modify paths part 2
* correct paths in each model's readme
- .gitattributes +7 -1
- README.md +15 -15
- models/face_detection_yunet/README.md +2 -2
- models/facial_expression_recognition/README.md +1 -1
- models/handpose_estimation_mediapipe/README.md +2 -2
- models/human_segmentation_pphumanseg/README.md +2 -2
- models/license_plate_detection_yunet/README.md +1 -1
- models/object_detection_nanodet/README.md +3 -3
- models/object_detection_yolox/README.md +3 -3
- models/object_tracking_dasiamrpn/README.md +1 -1
- models/palm_detection_mediapipe/README.md +1 -1
- models/person_detection_mediapipe/README.md +1 -1
- models/pose_estimation_mediapipe/README.md +1 -1
- models/qrcode_wechatqrcode/README.md +1 -1
- models/text_detection_db/README.md +2 -2
- models/text_recognition_crnn/README.md +2 -2
.gitattributes
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*.weights filter=lfs diff=lfs merge=lfs -text
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# ONNX
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.weights filter=lfs diff=lfs merge=lfs -text
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# ONNX
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*.onnx filter=lfs diff=lfs merge=lfs -text
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# Images
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.gif filter=lfs diff=lfs merge=lfs -text
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*.png filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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README.md
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### Face Detection with [YuNet](./models/face_detection_yunet/)
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 & [YOLOX](./models/object_detection_yolox/)
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### Facial Expression Recognition with [Progressive Teacher](./models/facial_expression_recognition/)
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### Human Segmentation with [PP-HumanSeg](./models/human_segmentation_pphumanseg/)
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### License Plate Detection with [LPD_YuNet](./models/license_plate_detection_yunet/)
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### Object Detection with [NanoDet](./models/object_detection_nanodet/) & [YOLOX](./models/object_detection_yolox/)
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### Object Tracking with [DaSiamRPN](./models/object_tracking_dasiamrpn/)
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### Palm Detection with [MP-PalmDet](./models/palm_detection_mediapipe/)
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### Hand Pose Estimation with [MP-HandPose](models/handpose_estimation_mediapipe/)
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### Person Detection with [MP-PersonDet](./models/person_detection_mediapipe)
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### Pose Estimation with [MP-Pose](models/pose_estimation_mediapipe)
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### QR Code Detection and Parsing with [WeChatQRCode](./models/qrcode_wechatqrcode/)
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### Chinese Text detection [DB](./models/text_detection_db/)
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### English Text detection [DB](./models/text_detection_db/)
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### Text Detection with [CRNN](./models/text_recognition_crnn/)
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## License
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models/face_detection_yunet/README.md
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### Example outputs
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## License
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models/facial_expression_recognition/README.md
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Note: Zoom in to to see the recognized facial expression in the top-left corner of each face boxes.
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## License
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models/handpose_estimation_mediapipe/README.md
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This model estimates 21 hand keypoints per detected hand from [palm detector](../palm_detection_mediapipe). (The image below is referenced from [MediaPipe Hands Keypoints](https://github.com/tensorflow/tfjs-models/tree/master/hand-pose-detection#mediapipe-hands-keypoints-used-in-mediapipe-hands))
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. (The image below is referenced from [MediaPipe Hands Keypoints](https://github.com/tensorflow/tfjs-models/tree/master/hand-pose-detection#mediapipe-hands-keypoints-used-in-mediapipe-hands))
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This model is converted from TFlite to ONNX using following tools:
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- TFLite model to ONNX: https://github.com/onnx/tensorflow-onnx
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### Example outputs
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## License
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models/human_segmentation_pphumanseg/README.md
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### Example outputs
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### Example outputs
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---
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Results of accuracy evaluation with [tools/eval](../../tools/eval).
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models/license_plate_detection_yunet/README.md
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### Example outputs
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## License
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models/object_detection_nanodet/README.md
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Here are some of the sample results that were observed using the model,
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Video inference result,
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Check [benchmark/download_data.py](../../benchmark/download_data.py) for the original images.
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Video inference result,
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## Model metrics:
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models/object_detection_yolox/README.md
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Here are some of the sample results that were observed using the model (**yolox_s.onnx**),
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Here are some of the sample results that were observed using the model (**yolox_s.onnx**),
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Check [benchmark/download_data.py](../../benchmark/download_data.py) for the original images.
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models/object_tracking_dasiamrpn/README.md
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### Example outputs
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## License
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models/palm_detection_mediapipe/README.md
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### Example outputs
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## License
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models/person_detection_mediapipe/README.md
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### Example outputs
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## License
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models/pose_estimation_mediapipe/README.md
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### Example outputs
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## License
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models/qrcode_wechatqrcode/README.md
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### Example outputs
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## License
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models/text_detection_db/README.md
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### Example outputs
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## License
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models/text_recognition_crnn/README.md
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### Examples
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## License
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