DetectionMetrics v2 #233
DetectionMetrics v2 #233
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I have modified the project webpage to have a new entrypoint, which clearly states the current status and acknowledges v1 appropriately. Also, the previous docs are untouched and will still be accessible in https://jderobot.github.io/DetectionMetrics/v1 (not deployed yet). Here is an overview of the new docs' appearance: detection_metrics_docs.mp4The new automatically generated sphinx docs for the Python code are stored in I have also updated the README accordingly: |
README.md
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| ### Project webpage [here](https://jderobot.github.io/DetectionMetrics) | ||
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| *DetectionMetrics* is a family of toolkits designed to unify and streamline the evaluation of perception models across different frameworks and datasets. With the release of ***DetectionMetrics v1*** we introduced a versatile suite of tools focused on object detection, supporting cross-framework evaluation and analysis. [Cite our work](#cite) if you use it in your research! |
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Nice! We could move all the information related to v1 to the bottom of the README, with a clear reference or link at the beginning for easy navigation.
Since the paper references DetectionMetrics, we should make sure to include a mention of it in the README.
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Done. Can you check the new layout?
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| # DetectionMetrics | ||
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We could include an architecture diagram and a video of the application, as we had before. I think that's really useful for users.
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I've added a simple diagram showcasing the classes included in the library. As soon as I have some GUI ready I'll post a video!
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Just upgraded it
README.md
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| <tr> | ||
| <th><i>DetectionMetrics v2</i></th> | ||
| <th>💻 <a href="https://github.com/JdeRobot/DetectionMetrics">Code</a></th> | ||
| <th>🔧 <a href="/v2/installation">Installation</a></th> |
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I guess all this reference would work once we merge it
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my bad, relative paths won't work in README 😅 I've fixed it but it won't work until new pages are deployed
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| ### Common | ||
| Install your deep learning framework of preference in your environment. We have tested: |
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Is the application multiplatform?
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in the sense of different OSs?
detectionmetrics/models/torch.py
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| from PIL import Image | ||
| import torch | ||
| from torch.utils.data import DataLoader, Dataset | ||
| from torchvision.transforms import v2 |
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Reading the code below, I find this alias v2 a little strange.
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Fixed, we now import v2 as transforms, which is more self-explanatory and resembles classic torchvision usage
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| # DetectionMetrics |
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Since we're generating the new version, maybe we could move the docs/gh-pages to a new branch gh-pages to separate the docs from the actual application code. What do you think?
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I like the proposal. I'd try to merge it first and see if the current deployment works tho, because I have added plain HTML docs generated with Sphinx (docs/py_docs) and I'd like to check whether it's working or not (locally it does as shown in the video above)
A complete rewriting of DetectionMetrics focused on semantic segmentation (for now). The new approach is pure Python and provides classes that enable transparent access to different datasets (Rellis3D, GOOSE, our GAIA format) and tools for evaluation with different frameworks (PyTorch, Tensorflow).
More details are provided in the new
READMEfile.Tech stack
Pending infra
detectionmetricspackage to PyPIPending functionality:
Things to decide:
https://jderobot.github.io/DetectionMetrics/v1)