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2f7ee0a
1
Parent(s):
b9ff28b
Update app.py
Browse files
app.py
CHANGED
@@ -14,6 +14,12 @@ model_id = 'microsoft/Florence-2-large'
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model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True).eval()
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processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
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def run_example(task_prompt, image, text_input=None):
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if text_input is None:
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prompt = task_prompt
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@@ -103,19 +109,19 @@ def process_image(image, task_prompt, text_input=None):
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elif task_prompt == '<OD>':
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results = run_example(task_prompt, image)
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fig = plot_bbox(image, results['<OD>'])
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return "", fig
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elif task_prompt == '<DENSE_REGION_CAPTION>':
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results = run_example(task_prompt, image)
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fig = plot_bbox(image, results['<DENSE_REGION_CAPTION>'])
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return "", fig
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elif task_prompt == '<REGION_PROPOSAL>':
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results = run_example(task_prompt, image)
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fig = plot_bbox(image, results['<REGION_PROPOSAL>'])
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return "", fig
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elif task_prompt == '<CAPTION_TO_PHRASE_GROUNDING>':
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results = run_example(task_prompt, image, text_input)
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fig = plot_bbox(image, results['<CAPTION_TO_PHRASE_GROUNDING>'])
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return "", fig
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elif task_prompt == '<REFERRING_EXPRESSION_SEGMENTATION>':
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results = run_example(task_prompt, image, text_input)
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output_image = copy.deepcopy(image)
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@@ -130,7 +136,7 @@ def process_image(image, task_prompt, text_input=None):
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results = run_example(task_prompt, image, text_input)
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bbox_results = convert_to_od_format(results['<OPEN_VOCABULARY_DETECTION>'])
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fig = plot_bbox(image, bbox_results)
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return "", fig
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elif task_prompt == '<REGION_TO_CATEGORY>':
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results = run_example(task_prompt, image, text_input)
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return results, None
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model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True).eval()
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processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
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def fig_to_pil(fig):
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buf = io.BytesIO()
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fig.savefig(buf, format='png')
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buf.seek(0)
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return Image.open(buf)
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def run_example(task_prompt, image, text_input=None):
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if text_input is None:
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prompt = task_prompt
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elif task_prompt == '<OD>':
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results = run_example(task_prompt, image)
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fig = plot_bbox(image, results['<OD>'])
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return "", fig_to_pil(fig)
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elif task_prompt == '<DENSE_REGION_CAPTION>':
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results = run_example(task_prompt, image)
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fig = plot_bbox(image, results['<DENSE_REGION_CAPTION>'])
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return "", fig_to_pil(fig)
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elif task_prompt == '<REGION_PROPOSAL>':
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results = run_example(task_prompt, image)
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fig = plot_bbox(image, results['<REGION_PROPOSAL>'])
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return "", fig_to_pil(fig)
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elif task_prompt == '<CAPTION_TO_PHRASE_GROUNDING>':
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results = run_example(task_prompt, image, text_input)
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fig = plot_bbox(image, results['<CAPTION_TO_PHRASE_GROUNDING>'])
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return "", fig_to_pil(fig)
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elif task_prompt == '<REFERRING_EXPRESSION_SEGMENTATION>':
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results = run_example(task_prompt, image, text_input)
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output_image = copy.deepcopy(image)
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results = run_example(task_prompt, image, text_input)
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bbox_results = convert_to_od_format(results['<OPEN_VOCABULARY_DETECTION>'])
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fig = plot_bbox(image, bbox_results)
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return "", fig_to_pil(fig)
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elif task_prompt == '<REGION_TO_CATEGORY>':
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results = run_example(task_prompt, image, text_input)
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return results, None
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