Comments (8)
@marco-c What exactly are we looking for in the documentation? Should i start with #2 and elaborate on the problem statement first for a start?
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I'm working on this myself. If you want, you can improve on the documentation I'm writing.
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@marco-c Alright
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This is now fixed, feel free to suggest additions if you want.
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@marco-c I had two suggestions for the documentation, one if we can document how to run the project locally? and the other if we could add a few lines at the top which talk about web compatibility briefly and then redirecting to some other page for some extra info.
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@marco-c I had two suggestions for the documentation, one if we can document how to run the project locally?
What would you write?
and the other if we could add a few lines at the top which talk about web compatibility briefly and then redirecting to some other page for some extra info.
There's a link now that brings you to a description of Web Compatibility.
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@marco-c
Something after get dependencies that the train / pretrain.py can be run directly to check how the current network fairs?
and also updating the structure of the project to explain about the rest of the files which have come up recently ? or is that not required?
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Something after get dependencies that the train / pretrain.py can be run directly to check how the current network fairs?
I think this should be clear from the description of the structure of the project, but we can add a short sentence.
and also updating the structure of the project to explain about the rest of the files which have come up recently ? or is that not required?
It's not required, but not forbidden either 😄
Feel free to submit PRs for any addition you think worth adding.
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Related Issues (20)
- Sort labels when saving them
- test_labels should validate all labels files
- test_labels.py is not actually testing the screenshots actually exist HOT 3
- Limit size of full page screenshot HOT 4
- Script to rename images and labels according to new convention
- Implementing Object Segmentation networks for bounding box annotations HOT 1
- Throw a meaningful error in utils.read_labels when labels.csv is empty HOT 2
- Running pretrain.py gives FileNotFoundError. HOT 4
- Try training a neural network using the responses from a DOM-based tool as features
- Try using the responses from a DOM-based tool as additional features
- Create a web-based tool to show predicted differences HOT 2
- Move the labeling tool to be web-based
- Use multiple releases of each browser
- Try using mdn/browser-compat-data to automatically label screenshot pairs
- Investigate training a model to detect regressions in a browser
- When prefilling an issue on webcompat.com, prefill as much as possible
- Add possibility to navigate to websites on demand
- Use Docker to run browsers and collect screenshots
- Train a baseline classifier HOT 12
- Out of memory error while training vgg16 and vgg19 with imagenet weights on Colab
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