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Update app.py
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app.py
CHANGED
@@ -28,35 +28,53 @@ def rand_image():
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def set_labels(text):
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return text.split(",")
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with gr.Blocks() as demo:
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with gr.
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demo.queue()
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demo.launch()
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def set_labels(text):
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return text.split(",")
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get_caption = gr.load("ryaalbr/caption", src="spaces")
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def generate_text(image):
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return get_caption(image)
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with gr.Blocks() as demo:
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with gr.Tab("Zero-Shot Classification"):
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labels = gr.State([]) # creates hidden component that can store a value and can be used as input/output; here, initial value is an empty list
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instructions = """## Instructions:
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1. Enter list of labels separated by commas (or select one of the examples below)
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2. Click **Get Random Image** to grab a random image from dataset and analyze it against the labels
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3. Click **Re-Classify Image** to re-run classification on current image after changing labels"""
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gr.Markdown(instructions)
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with gr.Row(variant="compact"):
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label_text = gr.Textbox(show_label=False, placeholder="Enter classification labels").style(container=False)
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#submit_btn = gr.Button("Submit").style(full_width=False)
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gr.Examples(["spring, summer, fall, winter",
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"mountain, city, beach, ocean, desert, forest, valley",
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"red, blue, green, white, black, purple, brown",
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"person, animal, landscape, something else",
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"day, night, dawn, dusk"], inputs=label_text)
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with gr.Row():
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with gr.Column(variant="panel"):
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im = gr.Image(interactive=False).style(height=height)
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with gr.Row():
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get_btn = gr.Button("Get Random Image").style(full_width=False)
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reclass_btn = gr.Button("Re-Classify Image").style(full_width=False)
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cf = gr.Label()
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#submit_btn.click(fn=set_labels, inputs=label_text)
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label_text.change(fn=set_labels, inputs=label_text, outputs=labels) # parse list if changed
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label_text.blur(fn=set_labels, inputs=label_text, outputs=labels) # parse list if focus is moved elsewhere; ensures that list is fully parsed before classification
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label_text.submit(fn=set_labels, inputs=label_text, outputs=labels) # parse list if user hits enter; ensures that list is fully parsed before classification
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get_btn.click(fn=rand_image, outputs=im)
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im.change(predict, inputs=[im, labels], outputs=cf)
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reclass_btn.click(predict, inputs=[im, labels], outputs=cf)
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with gr.Tab("Image Captioning"):
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with gr.Row():
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with gr.Column(variant="panel"):
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im_cap = gr.Image(interactive=False).style(height=height)
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with gr.Row():
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get_btn_cap = gr.Button("Get Random Image").style(full_width=False)
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caption_btn = gr.Button("Create Caption").style(full_width=False)
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caption = gr.Text()
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get_btn_cap.click(fn=rand_image, outputs=im_cap)
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#im_cap.change(generate_text, inputs=im_cap, outputs=caption)
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caption_btn.click(generate_text, inputs=im_cap, outputs=caption)
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demo.queue()
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demo.launch()
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