Comments (4)
@shiangyoung just get the predictions out of the network and write a script for visualization.
You will ned to save predicted_joints
. Yo can check evaluate_pcp()
to see how predicted joints are calculated.
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Hi @asanakoy,
We are currently running some tests however the predicted joints that we receive back is inaccurate. Could I ask if we are required to annotate the images before using them for testing?
Thank you for your earlier feedback.
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@shiangyoung as I understood you right, for testing you need annotations only to get a PCP/PCKh score.
You need to train until the net converges.
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Hi @asanakoy,
Yup, we are currently training and it has reached around 220k steps. From what I understand, it would then be possible to use our own image for prediction without any prior annotations? We are actually aiming to get a visualization of the prediction using our own image.
Thanks.
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Related Issues (20)
- IndexError: list index out of range HOT 5
- mpii dataset iteration HOT 1
- Error during testing data. HOT 3
- How can I get image like this? HOT 1
- not a bug... but a question HOT 1
- Error "Invalid argument" running on windows, python 3.5 HOT 1
- Test bbox extension range HOT 1
- Error while installing cupy HOT 1
- issue while importing scripts.config HOT 3
- predicting specific parts
- How to realize next stages?
- the maii dataset
- Syntax error
- Regarding Tensorflow 1.0
- bvlc_alexnet.tf cannot be download.
- Syntax error near uenxpected token '(' when running examples/train_mpii_alexnet_imagenet.py
- Train error does not decrease.
- 260k interations, mPCP on LSP is close to 0.42 with Imagenet initialization HOT 3
- Prediction for Real Time Video HOT 1
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