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Update app.py
Browse files
app.py
CHANGED
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@@ -50,24 +50,72 @@ def get_video_svd(image_in):
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print(result)
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return result[0]["video"]
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def infer(image_in, conditional_pose, prompt, chosen_model):
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iid_img = get_instantID(image_in, conditional_pose, prompt)
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if chosen_model == "i2vgen-xl" :
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video_res = get_video_i2vgen(iid_img, prompt)
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elif chosen_model == "stable-video" :
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video_res = get_video_svd(image_in)
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print(video_res)
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return video_res
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gr.
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gr.
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print(result)
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return result[0]["video"]
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def infer(image_in, camera_shot, conditional_pose, prompt, chosen_model):
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if camera_shot == "custom":
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if conditional_pose != None:
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conditional_pose = conditional_pose
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else :
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raise gr.Error("No custom conditional shot found !")
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else :
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if camera_shot == "close-up" :
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#
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elif camera_shot == "medium close-up":
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#
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elif camera_shot == "medium shot":
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#
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elif camera_shot == "cowboy shot":
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#
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elif camera_shot == "medium full shot":
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#
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elif camera_shot == "full shot":
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#
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iid_img = get_instantID(image_in, conditional_pose, prompt)
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if chosen_model == "i2vgen-xl" :
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video_res = get_video_i2vgen(iid_img, prompt)
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elif chosen_model == "stable-video" :
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video_res = get_video_svd(image_in)
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print(video_res)
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return video_res
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with gr.Blocks as demo:
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with gr.Column():
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gr.HTML("""
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""")
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with gr.Row():
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with gr.Column():
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face_in = gr.Image(type="filepath", label="Face to copy")
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camera_shot = gr.Dropdown(
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label = "Camera Shot",
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info = "Use standard camera shots vocabulary, or drop your custom shot as conditional pose (1280*720 ratio is recommended)"
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choices = [
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"custom", "close-up", "medium close-up", "medium shot", "cowboy shot", "medium full shot", "full shot"
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],
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value = "custom"
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)
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condition_shot = gr.Image(type="filepath", label="Custom conditional shot (Optional)")
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prompt = gr.Textbox(label="Prompt")
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chosen_model = gr.Radio(label="Choose a model", choices=["i2vgen-xl", "stable-video"], value="i2vgen-xl", interactive=False, visible=False)
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submit_btn = gr.Button("Submit")
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with gr.Column():
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video_out = gr.Video()
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submit_btn.click(
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fn = infer,
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inputs = [
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face_in,
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camera_shot,
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condition_shot,
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prompt,
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chosen_model
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],
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outputs = [
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video_out
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]
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)
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demo.queue(max_size=6).launch(debug=True)
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