Models included in /model-tfjs-graph-* were converted to TFJS Graph model format from the original repository
Models descriptors have been additionally parsed for readability
Actual model parsing implementation in efficientpose.js does not follow original
and is implemented using native TFJS ops and optimized for JavaScript execution
Function processResults() takes model.execute output and returns array of 16 keypoints:
- id
- score: score as number
- label: annotated body part as string
- xRaw: x coordinate normalized to 0..1
- yRaw: y coordinate normalized to 0..1
- x: x coordinate normalized to input image size
- y: y coordinate normalized to input image size
node efficientpose.js body.jpg2021-03-24 15:41:37 INFO: efficientpose version 0.0.1
2021-03-24 15:41:37 INFO: User: vlado Platform: linux Arch: x64 Node: v15.12.0
2021-03-24 15:41:37 INFO: Loaded model { modelPath: 'file://models/iv/efficientpose.json', minScore: 0.2 } tensors: 955 bytes: 25643252
2021-03-24 15:41:37 INFO: Model Signature {
inputs: { input_res1: { name: 'input_res1', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '600' }, { size: '600' }, { size: '3' } } } },
outputs: { 'upscaled_confs/BiasAdd:0': { name: 'upscaled_confs/BiasAdd:0', dtype: 'DT_FLOAT', tensorShape: { dim: [ { size: '1' }, { size: '-1' }, { size: '-1' }, { size: '16' } } } }
}
2021-03-24 15:41:37 INFO: Loaded image: body.jpg inputShape: [ 1024, 1024, 3 ] modelShape: [ 1, 600, 600, 3 ] decoded size: 3145728
2021-03-24 15:41:39 DATA: Results: [
{ id: 0, score: 0.8234584331512451, label: 'head', xRaw: 0.4033333333333333, yRaw: 0.051666666666666666, x: 413, y: 53 },
{ id: 1, score: 0.8789138197898865, label: 'neck', xRaw: 0.4533333333333333, yRaw: 0.18166666666666667, x: 464, y: 186 },
{ id: 2, score: 0.8490188717842102, label: 'rightShoulder', xRaw: 0.395, yRaw: 0.205, x: 404, y: 210 },
{ id: 3, score: 0.8640593886375427, label: 'rightElbow', xRaw: 0.40166666666666667, yRaw: 0.3333333333333333, x: 411, y: 341 },
{ id: 4, score: 0.8743583559989929, label: 'rightWrist', xRaw: 0.4066666666666667, yRaw: 0.45666666666666667, x: 416, y: 468 },
{ id: 5, score: 0.8736196756362915, label: 'chest', xRaw: 0.46166666666666667, yRaw: 0.21166666666666667, x: 473, y: 217 },
{ id: 6, score: 0.8904648423194885, label: 'leftShoulder', xRaw: 0.5283333333333333, yRaw: 0.215, x: 541, y: 220 },
{ id: 7, score: 0.9026476144790649, label: 'leftElbow', xRaw: 0.525, yRaw: 0.3616666666666667, x: 538, y: 370 },
{ id: 8, score: 0.7956844568252563, label: 'leftWrist', xRaw: 0.47333333333333333, yRaw: 0.49166666666666664, x: 485, y: 503 },
{ id: 9, score: 0.8972961902618408, label: 'pelvis', xRaw: 0.5066666666666667, yRaw: 0.45666666666666667, x: 519, y: 468 },
{ id: 10, score: 0.807637631893158, label: 'rightHip', xRaw: 0.4666666666666667, yRaw: 0.45666666666666667, x: 478, y: 468 },
{ id: 11, score: 0.8232259750366211, label: 'rightKnee', xRaw: 0.47833333333333333, yRaw: 0.63, x: 490, y: 645 },
{ id: 12, score: 0.9226986765861511, label: 'rightAnkle', xRaw: 0.43833333333333335, yRaw: 0.79, x: 449, y: 809 },
{ id: 13, score: 0.7791210412979126, label: 'leftHip', xRaw: 0.545, yRaw: 0.4533333333333333, x: 558, y: 464 },
{ id: 14, score: 0.8537712097167969, label: 'leftKnee', xRaw: 0.5883333333333334, yRaw: 0.65, x: 602, y: 666 },
{ id: 15, score: 0.8724350333213806, label: 'leftAnkle', xRaw: 0.6016666666666667, yRaw: 0.8433333333333334, x: 616, y: 864 },
]
2021-03-24 15:41:39 STATE: Created output image: outputs/body.jpg size: [ 1024, 1024 ]Original: https://github.com/daniegr/EfficientPose
Edit requirements.txt to remove specific version pinning and install required packages:
sudo apt install libmediainfo-dev
pip install -r requirements.txt
pip install tensorflowjsEdit track.py to fix tensor names:
# TensorFlow
elif framework in ['tensorflow', 'tf']:
output_tensor = model.graph.get_tensor_by_name('upscaled_confs/BiasAdd:0')
if lite:
batch_outputs = model.run(output_tensor, {'input_1_0:0': batch})
else:
batch_outputs = model.run(output_tensor, {'input_res1:0': batch})Run test:
python track.py --path=body.jpg --model=II_Lite --framework=tensorflow --visualize --storeFrom TensorFlow Frozen model to TFJS Graph model:
tensorflowjs_converter \
--input_format tf_frozen_model \
--output_format tfjs_graph_model \
--strip_debug_ops=* \
--weight_shard_size_bytes=16777216 \
--output_node_names='upscaled_confs/BiasAdd:0' \
tensorflow/EfficientPoseII_LITE.pb \
tfjs/ii-liteAfter conversion, lets add correct model signature in model.json
"signature": {
"inputs": { "input_1_0": { "name": "input_1_0", "dtype": "DT_FLOAT", "tensorShape":{"dim":[{"size":"1"},{"size":"368"},{"size":"368"},{"size":"3"}]} } },
"outputs": { "upscaled_confs/BiasAdd:0": { "name": "upscaled_confs/BiasAdd:0", "dtype": "DT_FLOAT", "tensorShape":{"dim":[{"size":"1"},{"size":"-1"},{"size":"-1"},{"size":"16"}]} } }
},
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