Comments (2)
mgyong
commented on May 4, 2024
The models we have just provides 21 landmarks on the hand. Pls read the Google AI blog post for more info. It is not possible for you to train new gestures using the tflite file we have provided. What new gestures are you looking to train? @fanzhanggoogle FYI
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gabrielstuff
commented on May 4, 2024
hello @qgh1223,
Could you share what you end up doing for gesture recognition ? As replied there: #40, I think that we could do some basic vptree and distance computation to find what hand pose match the other ones.
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Related Issues (20)
- Failed to get LLM params: INVALID_ARGUMENT: LLM model file is null HOT 6
- In my Flutter project, I use the blaze_face_short_range.tflite model and get output in the format [1, 896, 16] and [1, 896, 1]. Tell me how I can turn them into coordinates. HOT 4
- Selfie Segmentation vs Image Segmentation HOT 2
- Google Meet's model (image_segmenter) HOT 1
- Availability of previous version wheels HOT 3
- Detection of non-existent landmarks HOT 1
- Mediapipe with WebGL2... HOT 5
- MediaPipe shouldn't resize the external canvas HOT 3
- hair segmetation through medipipe code in python HOT 6
- Hair segmentation : ValueError: could not broadcast input array from shape (3,) into shape (337,325,4) HOT 3
- difference in results for landmarks and world_landmarks HOT 1
- <uses-native-library> missing in Android LLM Inference Guide HOT 3
- Allow cancelling ongoing async generation in LlmInference HOT 3
- Integrate MediaPipeTasksVision into dynamic framework throws Undefined symbols error HOT 1
- When will the new, improved blendshape prediction model v3 be implemented into Mediapipe? HOT 1
- Pose model failure reason
- Eyebrow Segmentation with Mediapipe in Python HOT 1
- online web demo yields better hand detection than its python equivalent HOT 4
- It is incorrect of using pose_landmark_full.tflite inference HOT 7
- Can't use MediaPipe in VisionOS development HOT 4
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