Evaluate custom and HuggingFace text-to-image/zero-shot-image-classification models like CLIP, SigLIP, DFN5B, and EVA-CLIP. Metrics include Zero-shot accuracy, Linear Probe, Image retrieval, and KNN accuracy.
Use an internal project json to record the label rows that have been completely downloaded, thus avoiding any further check on their images. Also, after the first time the image files and labels are calculated they will be saved for easy access in future runs.
Also, label rows' contents that are already up-to-date won't be downloaded again, even when overwrite_annotations is set to True (via last edited datetime comparison).
Use an internal project json to record the label rows that have been completely downloaded, thus avoiding any further check on their images. Also, after the first time the image files and labels are calculated they will be saved for easy access in future runs.
Also, label rows' contents that are already up-to-date won't be downloaded again, even when
overwrite_annotations
is set toTrue
(via last edited datetime comparison).