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update readme with w&b guide
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README.md
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@@ -140,13 +140,19 @@ res = module._compute(payload, max_iou=0.5, recognition_thresholds=[0.3, 0.5, 0.
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module.wandb(res,log_plots=True, debug=True)
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```
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/65ca2aafdc38a2858aa43f1e/RYEsFwt6K-jP0mp7_RIZv.png)
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/65ca2aafdc38a2858aa43f1e/zVbKzrURGYV858rpnOt_Q.png)
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-
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## Citations
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```bibtex {"id":"01HPS3ASFJXVQR88985GKHAQRE"}
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module.wandb(res,log_plots=True, debug=True)
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```
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- If `log_plots` is `True`, the W&B logging function generates four bar plots:
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- **Recognition metrics**
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- **Recognized metrics**
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- **Evaluation metrics** (F1, precision, recall)
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- **Confusion metrics** (false negatives, false positives, true positives)
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- If `debug` is `True`, the function logs the global metrics plus the per-sequence evaluation metrics in descending order of F1 score under the **Logs** section of the run page.
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- If both `log_plots` and `debug` are `False`, the function logs the metrics to the **Summary**.
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/65ca2aafdc38a2858aa43f1e/RYEsFwt6K-jP0mp7_RIZv.png)
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## Citations
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```bibtex {"id":"01HPS3ASFJXVQR88985GKHAQRE"}
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