Image Captioning
Generates a natural-language description of the uploaded image using an encoder–decoder vision-to-text model.
model: Xenova/vit-gpt2-image-captioningZero-Shot Object Detection
Define any set of objects to look for — the model locates and draws bounding boxes around them in the image above, even for categories it wasn't explicitly trained to detect.
model: Xenova/owlvit-base-patch32Zero-Shot Classification
Define any set of candidate labels — the model has never been trained on them specifically, yet ranks them by visual-semantic similarity via CLIP's shared embedding space.
model: Xenova/clip-vit-base-patch32Optical Character Recognition
Extracts printed text from the image using a transformer-based OCR model. Works best on clear, printed (not handwritten) text.
model: Xenova/trocr-small-printedSemantic Image Search
Upload a batch of images to build a gallery, then search it with a natural-language query. Each image is scored against your query in CLIP's shared embedding space and ranked by relevance — no keywords or tags required.
model: Xenova/clip-vit-base-patch32 (shared with Classify)