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app.py
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@@ -41,7 +41,7 @@ def infer(
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##### Also returns bounding boxes with their labels
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def parse_segmentation(input_image, input_text):
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out = infer(input_image, input_text, max_new_tokens=
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objs = extract_objs(out.lstrip("\n"), input_image.size[0], input_image.size[1], unique_labels=True)
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labels = set(obj.get('name') for obj in objs if obj.get('name'))
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color_map = {l: COLORS[i % len(COLORS)] for i, l in enumerate(labels)}
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@@ -83,20 +83,21 @@ for detailed information how to use and fine-tune PaliGemma models.
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"""
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with gr.Blocks(css="style.css") as demo:
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gr.Markdown(INTRO_TEXT)
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with gr.Tab("Text Generation"):
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with gr.
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text_input = gr.Text(label="Input Text")
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text_output = gr.Text(label="Text Output")
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label="Max New Tokens",
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info="Set to larger for longer generation.",
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minimum=10,
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maximum=
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value=20,
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step=10,
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)
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@@ -134,15 +135,19 @@ with gr.Blocks(css="style.css") as demo:
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inputs=chat_inputs,
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)
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with gr.Tab("Segment/Detect"):
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examples = [["./examples/
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["./examples/bee.jpg", "detect bee"],
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["./examples/barsik.jpg", "segment cat"],
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gr.Markdown("Example images are licensed CC0 by [akolesnikoff@](https://github.com/akolesnikoff), [mbosnjak@](https://github.com/mbosnjak), [maximneumann@](https://github.com/maximneumann) and [merve](https://huggingface.co/merve).")
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gr.Examples(
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examples=examples,
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##### Also returns bounding boxes with their labels
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def parse_segmentation(input_image, input_text):
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out = infer(input_image, input_text, max_new_tokens=200)
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objs = extract_objs(out.lstrip("\n"), input_image.size[0], input_image.size[1], unique_labels=True)
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labels = set(obj.get('name') for obj in objs if obj.get('name'))
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color_map = {l: COLORS[i % len(COLORS)] for i, l in enumerate(labels)}
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"""
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with gr.Blocks(theme=gr.themes.Soft(),css="style.css") as demo:
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gr.Markdown(INTRO_TEXT)
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with gr.Tab("Text Generation"):
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with gr.Row():
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with gr.Column():
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image = gr.Image(type="pil", width=512, height=512)
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text_input = gr.Text(label="Input Text")
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with gr.Column():
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text_output = gr.Text(label="Text Output")
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chat_btn = gr.Button()
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tokens = gr.Slider(
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label="Max New Tokens",
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info="Set to larger for longer generation.",
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minimum=10,
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maximum=200,
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value=20,
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step=10,
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)
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inputs=chat_inputs,
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)
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with gr.Tab("Segment/Detect"):
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with gr.Row():
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with gr.Column():
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image = gr.Image(type="pil")
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seg_input = gr.Text(label="Entities to Segment/Detect")
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seg_btn = gr.Button("Submit")
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with gr.Column():
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annotated_image = gr.AnnotatedImage(label="Output")
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examples = [["./examples/venice.jpg", "detect bird"],
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["./examples/cats.png", "segment cats"],
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["./examples/bee.jpg", "detect bee"],
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["./examples/barsik.jpg", "segment cat"],
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]
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gr.Markdown("Example images are licensed CC0 by [akolesnikoff@](https://github.com/akolesnikoff), [mbosnjak@](https://github.com/mbosnjak), [maximneumann@](https://github.com/maximneumann) and [merve](https://huggingface.co/merve).")
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gr.Examples(
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examples=examples,
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