Create app.py

app.py

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+import gradio as gr
+from gradio_client import Client
+
+def get_speech(text, voice):
+    try:
+        client = Client("https://collabora-whisperspeech.hf.space/")
+        result = client.predict(
+            text,   # str  in 'Enter multilingual text💬📝' Textbox component
+            voice,  # filepath  in 'Upload or Record Speaker Audio (optional)🌬️💬' Audio component
+            "",     # str  in 'alternatively, you can paste in an audio file URL:' Textbox component
+            14,     # float (numeric value between 10 and 15) in 'Tempo (in characters per second)' Slider component
+            api_name="/whisper_speech_demo"
+        )
+        print(result)
+        return result
+    except ValueError as e:
+        raise gr.Error(f"Error in get_speech: {str(e)}")
+
+def get_dreamtalk(image_in, speech):
+    try:
+        client = Client("https://fffiloni-dreamtalk.hf.space/")
+        result = client.predict(
+            speech, # filepath  in 'Audio input' Audio component
+            image_in,   # filepath  in 'Image' Image component
+            "M030_front_neutral_level1_001.mat",   # Literal in 'emotional style' Dropdown component
+            api_name="/infer"
+        )
+        print(result)
+        return result['video']
+    except ValueError as e:
+        raise gr.Error(f"Error in get_dreamtalk: {str(e)}")
+
+def pipe(text, voice, image_in):
+    try:
+        speech = get_speech(text, voice)
+        video = get_dreamtalk(image_in, speech)
+        return video
+    except Exception as e:
+        raise gr.Error(f"An error occurred while processing: {str(e)}")
+
+with gr.Blocks() as demo:
+    with gr.Column():
+        gr.HTML("""
+        <h1 style="text-align: center;">
+        Talking Image 
+        </h1>
+        <p style="text-align: center;"></p>
+        <h3 style="text-align: center;">
+        Clone your voice and make your photos speak. 
+        </h3>
+        <p style="text-align: center;"></p>
+        """)
+        with gr.Row():
+            with gr.Column():
+                image_in = gr.Image(label="Portrait IN", type="filepath", value="./creatus.jpg")
+            with gr.Column():
+                voice = gr.Audio(type="filepath", label="Upload or Record Speaker audio (Optional voice cloning)")
+                text = gr.Textbox(label="text")
+                submit_btn = gr.Button('Submit')
+            with gr.Column():
+                video_o = gr.Video(label="Video result")
+    submit_btn.click(
+        fn=pipe,
+        inputs=[text, voice, image_in],
+        outputs=[video_o],
+        concurrency_limit=3
+    )
+demo.queue(max_size=10).launch(show_error=True, show_api=False)