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Runtime error
Runtime error
Update app.py
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app.py
CHANGED
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@@ -29,9 +29,9 @@ def get_video_res(img_path, audio_path, res_video_path, dynamic_scale=1.0):
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min_resolution = 512
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inference_steps = 25
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# Get audio duration (
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audio = AudioSegment.from_file(audio_path)
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duration = len(audio) / 1000.0 #
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face_info = pipe.preprocess(img_path, expand_ratio=expand_ratio)
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print(f"Face detection info: {face_info}")
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@@ -43,7 +43,7 @@ def get_video_res(img_path, audio_path, res_video_path, dynamic_scale=1.0):
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img_path = crop_image_path
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os.makedirs(os.path.dirname(res_video_path), exist_ok=True)
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-
#
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pipe.process(
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img_path,
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audio_path,
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@@ -52,6 +52,8 @@ def get_video_res(img_path, audio_path, res_video_path, dynamic_scale=1.0):
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inference_steps=inference_steps,
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dynamic_scale=dynamic_scale
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)
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else:
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return -1
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@@ -61,7 +63,7 @@ os.makedirs(tmp_path, exist_ok=True)
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os.makedirs(res_path, exist_ok=True)
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def process_sonic(image, audio, dynamic_scale):
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#
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if image is None:
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raise gr.Error("Please upload an image")
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if audio is None:
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@@ -75,7 +77,7 @@ def process_sonic(image, audio, dynamic_scale):
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if len(arr.shape) == 1:
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arr = arr[:, None]
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#
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audio_segment = AudioSegment(
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arr.tobytes(),
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frame_rate=sampling_rate,
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@@ -84,18 +86,18 @@ def process_sonic(image, audio, dynamic_scale):
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)
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audio_segment = audio_segment.set_frame_rate(sampling_rate)
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#
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image_path = os.path.abspath(os.path.join(tmp_path, f'{img_md5}.png'))
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audio_path = os.path.abspath(os.path.join(tmp_path, f'{audio_md5}.wav'))
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res_video_path = os.path.abspath(os.path.join(res_path, f'{img_md5}_{audio_md5}_{dynamic_scale}.mp4'))
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#
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if not os.path.exists(image_path):
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image.save(image_path)
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if not os.path.exists(audio_path):
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audio_segment.export(audio_path, format="wav")
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#
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if os.path.exists(res_video_path):
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print(f"Using cached result: {res_video_path}")
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return res_video_path
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@@ -103,7 +105,7 @@ def process_sonic(image, audio, dynamic_scale):
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print(f"Generating new video with dynamic scale: {dynamic_scale}")
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return get_video_res(image_path, audio_path, res_video_path, dynamic_scale)
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#
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def get_example():
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return []
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@@ -171,7 +173,7 @@ with gr.Blocks(css=css) as demo:
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elem_id="video_output"
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)
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#
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process_btn.click(
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fn=process_sonic,
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inputs=[image_input, audio_input, dynamic_scale],
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@@ -179,7 +181,7 @@ with gr.Blocks(css=css) as demo:
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api_name="animate"
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)
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#
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gr.Examples(
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examples=get_example(),
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fn=process_sonic,
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@@ -188,7 +190,7 @@ with gr.Blocks(css=css) as demo:
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cache_examples=False
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)
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# Footer
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gr.HTML("""
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<div style="text-align: center; margin-top: 2em;">
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<div style="margin-bottom: 1em;">
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@@ -203,5 +205,5 @@ with gr.Blocks(css=css) as demo:
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</div>
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""")
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#
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demo.launch(share=True)
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min_resolution = 512
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inference_steps = 25
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# Get audio duration (for logging)
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audio = AudioSegment.from_file(audio_path)
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duration = len(audio) / 1000.0 # Convert ms to seconds
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face_info = pipe.preprocess(img_path, expand_ratio=expand_ratio)
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print(f"Face detection info: {face_info}")
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img_path = crop_image_path
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os.makedirs(os.path.dirname(res_video_path), exist_ok=True)
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# Process the video (duration parameter removed)
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pipe.process(
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img_path,
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audio_path,
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inference_steps=inference_steps,
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dynamic_scale=dynamic_scale
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)
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# ★ 수정: 생성된 비디오 파일 경로를 반환하도록 함.
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return res_video_path
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else:
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return -1
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os.makedirs(res_path, exist_ok=True)
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def process_sonic(image, audio, dynamic_scale):
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# Input validation
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if image is None:
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raise gr.Error("Please upload an image")
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if audio is None:
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if len(arr.shape) == 1:
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arr = arr[:, None]
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# Create an audio segment from numpy array
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audio_segment = AudioSegment(
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arr.tobytes(),
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frame_rate=sampling_rate,
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)
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audio_segment = audio_segment.set_frame_rate(sampling_rate)
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# Generate file paths
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image_path = os.path.abspath(os.path.join(tmp_path, f'{img_md5}.png'))
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audio_path = os.path.abspath(os.path.join(tmp_path, f'{audio_md5}.wav'))
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res_video_path = os.path.abspath(os.path.join(res_path, f'{img_md5}_{audio_md5}_{dynamic_scale}.mp4'))
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# Save input files if they don't exist
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if not os.path.exists(image_path):
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image.save(image_path)
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if not os.path.exists(audio_path):
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audio_segment.export(audio_path, format="wav")
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# If cached video exists, return it; otherwise, generate a new one
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if os.path.exists(res_video_path):
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print(f"Using cached result: {res_video_path}")
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return res_video_path
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print(f"Generating new video with dynamic scale: {dynamic_scale}")
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return get_video_res(image_path, audio_path, res_video_path, dynamic_scale)
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# Dummy get_example function to prevent errors in examples section
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def get_example():
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return []
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elem_id="video_output"
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)
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# Process button click: when clicked, process_sonic() is called and its return value is sent to video_output.
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process_btn.click(
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fn=process_sonic,
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inputs=[image_input, audio_input, dynamic_scale],
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api_name="animate"
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)
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# Examples section
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gr.Examples(
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examples=get_example(),
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fn=process_sonic,
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cache_examples=False
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)
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# Footer with attribution and links
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gr.HTML("""
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<div style="text-align: center; margin-top: 2em;">
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<div style="margin-bottom: 1em;">
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</div>
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""")
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# To create a public link, share=True is set.
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demo.launch(share=True)
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