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  1. README.md +14 -1
README.md CHANGED
@@ -85,7 +85,10 @@ processor = AutoProcessor.from_pretrained("microsoft/Florence-2-base-ft", trust_
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  url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg?download=true"
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  image = Image.open(requests.get(url, stream=True).raw)
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- def run_example(prompt):
 
 
 
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  inputs = processor(text=prompt, images=image, return_tensors="pt")
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  generated_ids = model.generate(
@@ -169,6 +172,16 @@ prompt = <REGION_PROPOSAL>
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  run_example(prompt)
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  ```
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  for More detailed examples, please refer to [notebook](https://huggingface.co/microsoft/Florence-2-large/blob/main/sample_inference.ipynb)
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  </details>
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  url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg?download=true"
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  image = Image.open(requests.get(url, stream=True).raw)
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+ def run_example(prompt, text_input=None):
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+
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+ if text_input is not None:
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+ prompt = prompt + text_input
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  inputs = processor(text=prompt, images=image, return_tensors="pt")
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  generated_ids = model.generate(
 
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  run_example(prompt)
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  ```
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+ ### Caption to Phrase Grounding
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+ caption to phrase grounding task requires additional text input, i.e. caption.
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+
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+ Caption to phrase grounding results format:
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+ {'\<CAPTION_TO_PHRASE_GROUNDING>': {'bboxes': [[x1, y1, x2, y2], ...], 'labels': ['', '', ...]}}
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+ ```python
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+ task_prompt = '<CAPTION_TO_PHRASE_GROUNDING>'
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+ results = run_example(task_prompt, text_input="A green car parked in front of a yellow building.")
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+ ```
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+
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  for More detailed examples, please refer to [notebook](https://huggingface.co/microsoft/Florence-2-large/blob/main/sample_inference.ipynb)
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  </details>
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