| library_name: kerasformers | |
| pipeline_tag: zero-shot-object-detection | |
| license: apache-2.0 | |
| tags: | |
| - keras | |
| - kerasformers | |
| - grounding-dino | |
| - tf | |
| - jax | |
| - pytorch | |
| # grounding_dino_tiny | |
| Grounding DINO performs open-set, text-grounded object detection: a Swin backbone and a BERT text encoder feed a cross-modality transformer that grounds free-form text prompts to boxes. | |
| Pure-Keras 3 model in [kerasformers](https://github.com/IMvision12/KerasFormers). The repo is self-describing: `kf_config.json` holds the architecture and `tokenizer.json` the text tokenizer, so it loads by its Hub repo id (weights download automatically): | |
| ```python | |
| from kerasformers.models.grounding_dino import ( | |
| GroundingDinoDetect, | |
| GroundingDinoProcessor, | |
| ) | |
| model = GroundingDinoDetect.from_weights("kerasformers/grounding_dino_tiny") | |
| processor = GroundingDinoProcessor.from_weights("kerasformers/grounding_dino_tiny") | |
| inputs = processor(images=image, text="a cat. a remote control.") | |
| outputs = model(inputs) # logits + pred_boxes | |
| ``` | |