Update app.py
Browse files
app.py
CHANGED
@@ -66,13 +66,11 @@ def array_to_image_path(image_array, session_id):
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img.save(filename)
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return os.path.abspath(filename)
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# Function to upload the file to S3
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def upload_to_s3(file_name, bucket, object_name=None):
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"""Upload a file to an S3 bucket."""
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if object_name is None:
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object_name = file_name
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# Create an S3 client
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s3 = boto3.client('s3')
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try:
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@@ -87,14 +85,10 @@ def upload_to_s3(file_name, bucket, object_name=None):
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return False
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@spaces.GPU
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def run_showui(image, query):
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"""Main function for inference."""
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session_id = datetime.now().strftime("%Y%m%d_%H%M%S")
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image_path = array_to_image_path(image, session_id)
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# Upload the image to S3
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upload_to_s3(image_path, 'altair.storage', object_name=f"ootb/images/{os.path.basename(image_path)}")
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-
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messages = [
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{
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"role": "user",
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@@ -106,7 +100,6 @@ def run_showui(image, query):
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}
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]
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# Prepare inputs for the model
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global model
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model = model.to("cuda")
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@@ -121,7 +114,6 @@ def run_showui(image, query):
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)
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inputs = inputs.to("cuda")
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# Generate output
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generated_ids = model.generate(**inputs, max_new_tokens=128)
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generated_ids_trimmed = [
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out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
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@@ -130,50 +122,53 @@ def run_showui(image, query):
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generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
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)[0]
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# Parse the output into coordinates
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click_xy = ast.literal_eval(output_text)
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# Draw the point on the image
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result_image = draw_point(image_path, click_xy, radius=10)
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return result_image, str(click_xy), image_path
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-
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"vote_type": vote_type,
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"image_path": image_path,
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"query": query,
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"
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"timestamp": datetime.now().isoformat()
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}
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local_file_name = f"
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f.write(json.dumps(vote_data) + "\n")
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upload_to_s3(local_file_name, 'altair.storage', object_name=f"ootb/votes/{local_file_name}")
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return
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def handle_vote(vote_type, image_path, query, action_generated, session_id):
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"""Handle vote recording by using the consistent image path."""
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if image_path is None:
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return "No image uploaded. Please upload an image before voting."
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return record_vote(vote_type, image_path, query, action_generated, session_id)
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# Load logo and encode to Base64
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with open("./assets/showui.png", "rb") as image_file:
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base64_image = base64.b64encode(image_file.read()).decode("utf-8")
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# Define layout and UI
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def build_demo(embed_mode, concurrency_count=1):
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with gr.Blocks(title="ShowUI Demo", theme=gr.themes.Default()) as demo:
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# State to store the consistent image path
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state_image_path = gr.State(value=None)
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state_session_id = gr.State(value=None)
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@@ -181,15 +176,10 @@ def build_demo(embed_mode, concurrency_count=1):
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gr.HTML(
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f"""
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<div style="text-align: center; margin-bottom: 20px;">
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<!-- Image -->
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<div style="display: flex; justify-content: center;">
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<img src="data:image/png;base64,{base64_image}" alt="ShowUI" width="320" style="margin-bottom: 10px;"/>
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</div>
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<!-- Description -->
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<p>ShowUI is a lightweight vision-language-action model for GUI agents.</p>
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<!-- Links -->
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<div style="display: flex; justify-content: center; gap: 15px; font-size: 20px;">
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<a href="https://huggingface.co/showlab/ShowUI-2B" target="_blank">
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<img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-ShowUI--2B-blue" alt="model"/>
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@@ -207,7 +197,6 @@ def build_demo(embed_mode, concurrency_count=1):
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with gr.Row():
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with gr.Column(scale=3):
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# Input components
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imagebox = gr.Image(type="numpy", label="Input Screenshot")
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textbox = gr.Textbox(
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show_label=True,
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@@ -216,7 +205,6 @@ def build_demo(embed_mode, concurrency_count=1):
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)
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submit_btn = gr.Button(value="Submit", variant="primary")
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# Placeholder examples
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gr.Examples(
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examples=[
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["./examples/app_store.png", "Download Kindle."],
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@@ -234,9 +222,7 @@ def build_demo(embed_mode, concurrency_count=1):
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)
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with gr.Column(scale=8):
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# Output components
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output_img = gr.Image(type="pil", label="Output Image")
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# Add a note below the image to explain the red point
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gr.HTML(
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"""
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<p><strong>Note:</strong> The <span style="color: red;">red point</span> on the output image represents the predicted clickable coordinates.</p>
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@@ -244,39 +230,21 @@ def build_demo(embed_mode, concurrency_count=1):
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)
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output_coords = gr.Textbox(label="Clickable Coordinates")
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# Buttons for voting, flagging, regenerating, and clearing
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with gr.Row(elem_id="action-buttons", equal_height=True):
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downvote_btn = gr.Button(value="
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regenerate_btn = gr.Button(value="🔄 Regenerate", variant="secondary")
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clear_btn = gr.Button(value="🗑️ Clear", interactive=True) # Combined Clear button
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# Define button actions
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def on_submit(image, query):
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"""Handle the submit button click."""
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if image is None:
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raise ValueError("No image provided. Please upload an image before submitting.")
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result_image, click_coords, image_path
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return result_image, click_coords, image_path, session_id
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def on_image_upload(image):
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"""Generate a new session ID when a new image is uploaded."""
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if image is None:
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raise ValueError("No image provided. Please upload an image.")
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-
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return
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imagebox.upload(
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on_image_upload,
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inputs=imagebox,
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outputs=state_session_id,
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queue=False
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)
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submit_btn.click(
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on_submit,
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@@ -287,47 +255,26 @@ def build_demo(embed_mode, concurrency_count=1):
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clear_btn.click(
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lambda: (None, None, None, None, None),
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inputs=None,
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outputs=[imagebox, textbox, output_img, output_coords, state_image_path, state_session_id],
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queue=False
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)
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lambda
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[output_img, output_coords, state_image_path],
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)
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# Record vote actions without feedback messages
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vote_btn.click(
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lambda image_path, query, action_generated, session_id: handle_vote(
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"upvote", image_path, query, action_generated, session_id
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),
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inputs=[state_image_path, textbox, output_coords, state_session_id],
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outputs=[],
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queue=False
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)
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downvote_btn.click(
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lambda
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),
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inputs=[state_image_path, textbox, output_coords, state_session_id],
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outputs=[],
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queue=False
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)
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flag_btn.click(
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lambda image_path, query, action_generated, session_id: handle_vote(
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"flag", image_path, query, action_generated, session_id
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),
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inputs=[state_image_path, textbox, output_coords, state_session_id],
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outputs=[],
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queue=False
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)
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return demo
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# Launch the app
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if __name__ == "__main__":
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demo = build_demo(embed_mode=False)
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demo.queue(api_open=False).launch(
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server_port=7860,
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ssr_mode=False,
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debug=True,
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)
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img.save(filename)
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return os.path.abspath(filename)
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def upload_to_s3(file_name, bucket, object_name=None):
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"""Upload a file to an S3 bucket."""
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if object_name is None:
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object_name = file_name
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s3 = boto3.client('s3')
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try:
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return False
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@spaces.GPU
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def run_showui(image, query, session_id):
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"""Main function for inference."""
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image_path = array_to_image_path(image, session_id)
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messages = [
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{
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"role": "user",
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}
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]
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global model
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model = model.to("cuda")
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)
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inputs = inputs.to("cuda")
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generated_ids = model.generate(**inputs, max_new_tokens=128)
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generated_ids_trimmed = [
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out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
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generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
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)[0]
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click_xy = ast.literal_eval(output_text)
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result_image = draw_point(image_path, click_xy, radius=10)
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return result_image, str(click_xy), image_path
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def save_and_upload_data(image_path, query, session_id, votes=None):
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"""Save the data to a JSON file and upload to S3."""
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votes = votes or {"upvotes": 0, "downvotes": 0}
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data = {
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"image_path": image_path,
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"query": query,
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"votes": votes,
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"timestamp": datetime.now().isoformat()
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}
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local_file_name = f"data_{session_id}.json"
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with open(local_file_name, "w") as f:
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json.dump(data, f)
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upload_to_s3(local_file_name, 'altair.storage', object_name=f"ootb/{local_file_name}")
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return data
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def update_vote(vote_type, session_id):
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"""Update the vote count and re-upload the JSON file."""
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local_file_name = f"data_{session_id}.json"
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with open(local_file_name, "r") as f:
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data = json.load(f)
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if vote_type == "upvote":
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data["votes"]["upvotes"] += 1
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elif vote_type == "downvote":
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data["votes"]["downvotes"] += 1
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with open(local_file_name, "w") as f:
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json.dump(data, f)
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upload_to_s3(local_file_name, 'altair.storage', object_name=f"ootb/{local_file_name}")
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return f"Your {vote_type} has been recorded. Thank you!"
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with open("./assets/showui.png", "rb") as image_file:
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base64_image = base64.b64encode(image_file.read()).decode("utf-8")
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def build_demo(embed_mode, concurrency_count=1):
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with gr.Blocks(title="ShowUI Demo", theme=gr.themes.Default()) as demo:
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state_image_path = gr.State(value=None)
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state_session_id = gr.State(value=None)
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gr.HTML(
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f"""
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<div style="text-align: center; margin-bottom: 20px;">
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<div style="display: flex; justify-content: center;">
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<img src="data:image/png;base64,{base64_image}" alt="ShowUI" width="320" style="margin-bottom: 10px;"/>
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</div>
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<p>ShowUI is a lightweight vision-language-action model for GUI agents.</p>
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<div style="display: flex; justify-content: center; gap: 15px; font-size: 20px;">
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<a href="https://huggingface.co/showlab/ShowUI-2B" target="_blank">
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<img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-ShowUI--2B-blue" alt="model"/>
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with gr.Row():
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with gr.Column(scale=3):
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imagebox = gr.Image(type="numpy", label="Input Screenshot")
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textbox = gr.Textbox(
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show_label=True,
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)
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submit_btn = gr.Button(value="Submit", variant="primary")
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gr.Examples(
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examples=[
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["./examples/app_store.png", "Download Kindle."],
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)
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with gr.Column(scale=8):
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output_img = gr.Image(type="pil", label="Output Image")
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gr.HTML(
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"""
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<p><strong>Note:</strong> The <span style="color: red;">red point</span> on the output image represents the predicted clickable coordinates.</p>
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)
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output_coords = gr.Textbox(label="Clickable Coordinates")
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with gr.Row(elem_id="action-buttons", equal_height=True):
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upvote_btn = gr.Button(value="Looks good!", variant="secondary")
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downvote_btn = gr.Button(value="Too bad!", variant="secondary")
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clear_btn = gr.Button(value="🗑️ Clear", interactive=True)
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def on_submit(image, query):
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if image is None:
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raise ValueError("No image provided. Please upload an image before submitting.")
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session_id = datetime.now().strftime("%Y%m%d_%H%M%S")
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result_image, click_coords, image_path = run_showui(image, query, session_id)
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save_and_upload_data(image_path, query, session_id)
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return result_image, click_coords, image_path, session_id
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submit_btn.click(
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on_submit,
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clear_btn.click(
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lambda: (None, None, None, None, None),
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inputs=None,
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outputs=[imagebox, textbox, output_img, output_coords, state_image_path, state_session_id],
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queue=False
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)
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upvote_btn.click(
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lambda session_id: update_vote("upvote", session_id),
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inputs=state_session_id,
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outputs=[],
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queue=False
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)
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downvote_btn.click(
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lambda session_id: update_vote("downvote", session_id),
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inputs=state_session_id,
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outputs=[],
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queue=False
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)
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return demo
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if __name__ == "__main__":
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demo = build_demo(embed_mode=False)
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demo.queue(api_open=False).launch(
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server_port=7860,
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ssr_mode=False,
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debug=True,
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)
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