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@ -84,7 +84,7 @@ To check all the commands for the parser and the subparsers (including openpifpa
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or check the file `monoloco/run.py`
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or check the file `monoloco/run.py`
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# Predict
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# Prediction
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The predict script receives an image (or an entire folder using glob expressions),
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The predict script receives an image (or an entire folder using glob expressions),
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calls PifPaf for 2d human pose detection over the image
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calls PifPaf for 2d human pose detection over the image
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and runs Monoloco for 3d location of the detected poses.
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and runs Monoloco for 3d location of the detected poses.
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@ -140,7 +140,7 @@ The above gif has been obtained running on a Macbook the command:
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python3 -m monoloco.run predict --webcam --scale 0.2 --output_types combined --z_max 10 --checkpoint resnet50 --model data/models/monoloco-190513-1437.pkl
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python3 -m monoloco.run predict --webcam --scale 0.2 --output_types combined --z_max 10 --checkpoint resnet50 --model data/models/monoloco-190513-1437.pkl
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```
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```
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# Preprocess
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# Preprocessing
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### Datasets
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### Datasets
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@ -176,7 +176,7 @@ by the image name to easily access ground truth files for evaluation and predict
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# Train
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# Training
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Provide the json file containing the preprocess joints as argument.
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Provide the json file containing the preprocess joints as argument.
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As simple as `python3 -m monoloco.run --train --joints <json file path>`
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As simple as `python3 -m monoloco.run --train --joints <json file path>`
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@ -213,7 +213,8 @@ The average geometrical value for comparison can be obtained running:
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The following results are obtained running:
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The following results are obtained running:
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`python3 -m monoloco.run eval --model data/models/monoloco-190719-0923.pkl --generate
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`python3 -m monoloco.run eval --model data/models/monoloco-190719-0923.pkl --generate
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--dir_ann <folder containing pifpaf annotations of KITTI images>`
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--dir_ann <folder containing pifpaf annotations of KITTI images>`
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