Comments (2)
Eval only works with a trimap associated with the input image.
That is because the training of the model was also done with a trimap as an input. That trimap was generated from the ground truth, with erosion. Perhaps the same model with some modification could be trained without the Trimap.
However, we designed this model to be used as a postprocessing step to refine background extraction and produce output image with transparency, with the first step of generating the trimap done either manually or with a segmentation technique.
Sorry for the delay, and thanks for your interest!
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for your pre-trained model, would there be any detriment (or have you tried) using an automated tri-map generation algo? https://ieeexplore.ieee.org/document/6694178
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Related Issues (20)
- Download a U-net implementation and adapt it to our needs
- [Paper] Critical Analysis
- Evaluate the u-net
- [Paper] Experiments
- (If we have time) Adapt the logic to output the object instead of a mask
- [Paper] Theorical approach
- [Paper] Intro/related work
- Error message running Training HOT 6
- An error occurred while running the evaluation script HOT 5
- The output images have pink/red hue over it HOT 2
- Time required for training
- How long it did you take to train the modal? HOT 1
- train.py: module 'tensorflow' has no attribute 'get_variable' HOT 1
- Facing issues while using it in colab HOT 2
- Not able to download images HOT 4
- I didn't find the GAN part in the project HOT 1
- Item no.: 1 --> Item name = portrait transparent background Evaluating... Looks like we cannot locate the path the 'chromedriver' (use the '--chromedriver' argument to specify the path to the executable.) or google chrome browser is not installed on your machine (exception: Message: session not created: This version of ChromeDriver only supports Chrome version 81 )
- Is there anyone can download the
- Is there anyone can download the dataset?
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