Update app.py

app.py

@@ -1,217 +1,125 @@
 import os
-import platform
-import uuid
-import shutil
-from pydub import AudioSegment
-import spaces
-import torch
 import gradio as gr
-from huggingface_hub import snapshot_download
+from src.gradio_demo import SadTalker
 
-from examples.get_examples import get_examples
-from src.facerender.pirender_animate import AnimateFromCoeff_PIRender
-from src.utils.preprocess import CropAndExtract
-from src.test_audio2coeff import Audio2Coeff
-from src.facerender.animate import AnimateFromCoeff
-from src.generate_batch import get_data
-from src.generate_facerender_batch import get_facerender_data
-from src.utils.init_path import init_path
+try:
+    import webui  # in webui
+    IN_WEBUi = True
+except ImportError:
+    IN_WEBUi = False
 
-checkpoint_path = 'checkpoints'
-config_path = 'src/config'
-device = "cuda" if torch.cuda.is_available(
-) else "mps" if platform.system() == 'Darwin' else "cpu"
-
-os.environ['TORCH_HOME'] = checkpoint_path
-snapshot_download(repo_id='vinthony/SadTalker-V002rc',
-                  local_dir=checkpoint_path, local_dir_use_symlinks=True)
-
-
-def mp3_to_wav(mp3_filename, wav_filename, frame_rate):
-    AudioSegment.from_file(file=mp3_filename).set_frame_rate(
-        frame_rate).export(wav_filename, format="wav")
-
-
-@spaces.GPU(duration=120)
-def generate_video(source_image, driven_audio, preprocess='crop', still_mode=False, use_enhancer=False,
-                   batch_size=1, size=256, pose_style=0, facerender='facevid2vid', exp_scale=1.0,
-                   use_ref_video=False, ref_video=None, ref_info=None, use_idle_mode=False,
-                   length_of_audio=0, use_blink=True, result_dir='./results/'):
-    # Initialize models and paths
-    sadtalker_paths = init_path(
-        checkpoint_path, config_path, size, False, preprocess)
-    audio_to_coeff = Audio2Coeff(sadtalker_paths, device)
-    preprocess_model = CropAndExtract(sadtalker_paths, device)
-    animate_from_coeff = AnimateFromCoeff(sadtalker_paths, device) if facerender == 'facevid2vid' and device != 'mps' \
-        else AnimateFromCoeff_PIRender(sadtalker_paths, device)
-
-    # Create directories for saving results
-    time_tag = str(uuid.uuid4())
-    save_dir = os.path.join(result_dir, time_tag)
-    os.makedirs(save_dir, exist_ok=True)
-    input_dir = os.path.join(save_dir, 'input')
-    os.makedirs(input_dir, exist_ok=True)
-
-    # Process source image
-    pic_path = os.path.join(input_dir, os.path.basename(source_image))
-    shutil.move(source_image, input_dir)
-
-    # Process driven audio
-    if driven_audio and os.path.isfile(driven_audio):
-        audio_path = os.path.join(input_dir, os.path.basename(driven_audio))
-        if '.mp3' in audio_path:
-            mp3_to_wav(driven_audio, audio_path.replace('.mp3', '.wav'), 16000)
-            audio_path = audio_path.replace('.mp3', '.wav')
-        else:
-            shutil.move(driven_audio, input_dir)
-    elif use_idle_mode:
-        audio_path = os.path.join(
-            input_dir, 'idlemode_'+str(length_of_audio)+'.wav')
-        AudioSegment.silent(
-            duration=1000*length_of_audio).export(audio_path, format="wav")
+def toggle_audio_file(choice):
+    if not choice:
+        return gr.update("visible", True), gr.update("visible", False)
     else:
-        assert use_ref_video and ref_info == 'all'
+        return gr.update("visible", False), gr.update("visible", True)
 
-    # Process reference video
-    if use_ref_video and ref_info == 'all':
-        ref_video_videoname = os.path.splitext(os.path.split(ref_video)[-1])[0]
-        audio_path = os.path.join(save_dir, ref_video_videoname+'.wav')
-        os.system(
-            f"ffmpeg -y -hide_banner -loglevel error -i {ref_video} {audio_path}")
-        ref_video_frame_dir = os.path.join(save_dir, ref_video_videoname)
-        os.makedirs(ref_video_frame_dir, exist_ok=True)
-        ref_video_coeff_path, _, _ = preprocess_model.generate(
-            ref_video, ref_video_frame_dir, preprocess, source_image_flag=False)
+def ref_video_fn(path_of_ref_video):
+    if path_of_ref_video:
+        return gr.update("value", True)
     else:
-        ref_video_coeff_path = None
+        return gr.update("value", False)
 
-    # Preprocess source image
-    first_frame_dir = os.path.join(save_dir, 'first_frame_dir')
-    os.makedirs(first_frame_dir, exist_ok=True)
-    first_coeff_path, crop_pic_path, crop_info = preprocess_model.generate(
-        pic_path, first_frame_dir, preprocess, True, size)
-    if first_coeff_path is None:
-        raise AttributeError("No face is detected")
+def sadtalker_demo(checkpoint_path="checkpoints", config_path="src/config", warpfn=None):
+    sad_talker = SadTalker(checkpoint_path, config_path, lazy_load=True)
 
-    # Determine reference coefficients
-    ref_pose_coeff_path, ref_eyeblink_coeff_path = None, None
-    if use_ref_video:
-        if ref_info == 'pose':
-            ref_pose_coeff_path = ref_video_coeff_path
-        elif ref_info == 'blink':
-            ref_eyeblink_coeff_path = ref_video_coeff_path
-        elif ref_info == 'pose+blink':
-            ref_pose_coeff_path = ref_eyeblink_coeff_path = ref_video_coeff_path
-    else:
-        ref_pose_coeff_path = ref_eyeblink_coeff_path = None
-
-    # Generate coefficients from audio or reference video
-    if use_ref_video and ref_info == 'all':
-        coeff_path = ref_video_coeff_path
-    else:
-        batch = get_data(first_coeff_path, audio_path, device, ref_eyeblink_coeff_path=ref_eyeblink_coeff_path,
-                         still=still_mode, idlemode=use_idle_mode, length_of_audio=length_of_audio, use_blink=use_blink)
-        coeff_path = audio_to_coeff.generate(
-            batch, save_dir, pose_style, ref_pose_coeff_path)
-
-    # Generate video from coefficients
-    data = get_facerender_data(coeff_path, crop_pic_path, first_coeff_path, audio_path, batch_size, still_mode=still_mode,
-                               preprocess=preprocess, size=size, expression_scale=exp_scale, facemodel=facerender)
-    return_path = animate_from_coeff.generate(data, save_dir, pic_path, crop_info, enhancer='gfpgan' if use_enhancer else None,
-                                              preprocess=preprocess, img_size=size)
-    video_name = data['video_name']
-    print(f'The generated video is named {video_name} in {save_dir}')
-
-    return return_path
+    with gr.Blocks(analytics_enabled=False) as sadtalker_interface:
+        gr.markdown("<div align='center'> <h2> 😭 SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation (CVPR 2023) </span> \
+                    <a style='font-size:18px;color: #efefef' href='https://arxiv.org/abs/2211.12194'>Arxiv</a> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; \
+                    <a style='font-size:18px;color: #efefef' href='https://sadtalker.github.io'>Homepage</a>  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; \
+                     <a style='font-size:18px;color: #efefef' href='https://github.com/Winfredy/SadTalker'> Github </div>")
 
-
-# Gradio UI
-with gr.Blocks(analytics_enabled=False) as demo:
-    with gr.Row():
-        with gr.Column(variant='panel'):
-            with gr.Tabs(elem_id="sadtalker_source_image"):
-                with gr.TabItem('Source image'):
-                    with gr.Row():
-                        source_image = gr.Image(
-                            label="Source image", sources="upload", type="filepath", elem_id="img2img_image")
+        with gr.Row(style="equal_height: False"):
+            with gr.Column(variant="panel"):
+                with gr.Tabs(elem_id="sadtalker_source_image"):
+                    with gr.TabItem("Upload image"):
+                        with gr.Row():
+                            source_image = gr.Image(label="Source image", source="upload", type="filepath", elem_id="img2img_image", style="width: 512px")
 
             with gr.Tabs(elem_id="sadtalker_driven_audio"):
-                with gr.TabItem('Driving Methods'):
-                    gr.Markdown(
-                        "Possible driving combinations: <br> 1. Audio only 2. Audio/IDLE Mode + Ref Video(pose, blink, pose+blink) 3. IDLE Mode only 4. Ref Video only (all) ")
-
-                    with gr.Row():
-                        driven_audio = gr.Audio(
-                            label="Input audio", sources="upload", type="filepath")
-                        driven_audio_no = gr.Audio(
-                            label="Use IDLE mode, no audio is required", sources="upload", type="filepath", visible=False)
-
-                        with gr.Column():
-                            use_idle_mode = gr.Checkbox(
-                                label="Use Idle Animation")
-                            length_of_audio = gr.Number(
-                                value=5, label="The length(seconds) of the generated video.")
-                            use_idle_mode.change(lambda choice: (gr.update(visible=not choice), gr.update(visible=choice)),
-                                                 inputs=use_idle_mode, outputs=[driven_audio, driven_audio_no])
-
-                    with gr.Row():
-                        ref_video = gr.Video(
-                            label="Reference Video", sources="upload", elem_id="vidref")
-
-                        with gr.Column():
-                            use_ref_video = gr.Checkbox(
-                                label="Use Reference Video")
-                            ref_info = gr.Radio(['pose', 'blink', 'pose+blink', 'all'], value='pose', label='Reference Video',
-                                                info="How to borrow from reference Video?((fully transfer, aka, video driving mode))")
-
-                        ref_video.change(lambda path: gr.update(
-                            value=path is not None), inputs=ref_video, outputs=use_ref_video)
-
-        with gr.Column(variant='panel'):
-            with gr.Tabs(elem_id="sadtalker_checkbox"):
-                with gr.TabItem('Settings'):
-                    with gr.Column(variant='panel'):
-                        with gr.Row():
+                with gr.TabItem("Upload OR TTS"):
+                    with gr.Column(variant="panel"):
+                        driven_audio = gr.Audio(label="Input audio", source="upload", type="filepath")
+
+                if sys.platform != "win32" and not IN_WEBUi:
+                    from src.utils.text2speech import TTSTalker
+
+                    tts_talker = TTSTalker()
+                    with gr.Column(variant="panel"):
+                        input_text = gr.Textbox(
+                            label="Generating audio from text",
+                            lines=5,
+                            placeholder="Enter text for audio generation using @Coqui.ai TTS.",
+                        )
+                        tts = gr.Button("Generate audio", elem_id="sadtalker_audio_generate", variant="primary")
+                        tts.click(tts_talker.test, [input_text], [driven_audio])
+
+            with gr.Column(variant="panel"):
+                with gr.Tabs(elem_id="sadtalker_checkbox"):
+                    with gr.TabItem("Settings"):
+                        gr.markdown(
+                            "Need help? Visit our [best practice page](https://github.com/OpenTalker/SadTalker/blob/main/docs/best_practice.md) for details."
+                        )
+                        with gr.Column(variant="panel"):
+                            # width = gr.Slider(
+                            #     minimum=64,
+                            #     elem_id="img2img_width",
+                            #     maximum=2048,
+                            #     step=8,
+                            #     label="Manually Crop Width",
+                            #     value=512,
+                            # )  # img2img_width
+                            # height = gr.Slider(
+                            #     minimum=64,
+                            #     elem_id="img2img_height",
+                            #     maximum=2048,
+                            #     step=8,
+                            #     label="Manually Crop Height",
+                            #     value=512,
+                            # )  # img2img_width
                             pose_style = gr.Slider(
-                                minimum=0, maximum=45, step=1, label="Pose style", value=0)
-                            exp_weight = gr.Slider(
-                                minimum=0, maximum=3, step=0.1, label="expression scale", value=1)
-                            blink_every = gr.Checkbox(
-                                label="use eye blink", value=True)
-
-                        with gr.Row():
+                                minimum=0, maximum=46, step=1, label="Pose style", value=0
+                            )
                             size_of_image = gr.Radio(
-                                [256, 512], value=256, label='face model resolution', info="use 256/512 model?")
+                                [256, 512],
+                                value=256,
+                                label="face model resolution",
+                                info="Use 256/512 model?",
+                            )
                             preprocess_type = gr.Radio(
-                                ['crop', 'resize', 'full', 'extcrop', 'extfull'], value='crop', label='preprocess', info="How to handle input image?")
-
-                        with gr.Row():
+                                ["crop", "resize", "full", "extcrop", "extfull"],
+                                value="crop",
+                                label="preprocess",
+                                info="How to handle input image?",
+                            )
                             is_still_mode = gr.Checkbox(
-                                label="Still Mode (fewer head motion, works with preprocess `full`)")
-                            facerender = gr.Radio(
-                                ['facevid2vid', 'pirender'], value='facevid2vid', label='facerender', info="which face render?")
-
-                        with gr.Row():
+                                label="Still Mode (fewer head motion, works with preprocess `full`)"
+                            )
                             batch_size = gr.Slider(
-                                label="batch size in generation", step=1, maximum=10, value=1)
-                            enhancer = gr.Checkbox(
-                                label="GFPGAN as Face enhancer", value=True)
-
-                        submit = gr.Button(
-                            'Generate', elem_id="sadtalker_generate", variant='primary')
-
-            with gr.Tabs(elem_id="sadtalker_generated"):
-                gen_video = gr.Video(label="Generated video")
-
-    submit.click(
-        fn=generate_video,
-        inputs=[source_image, driven_audio, preprocess_type, is_still_mode, enhancer, batch_size, size_of_image,
-                pose_style, facerender, exp_weight, use_ref_video, ref_video, ref_info, use_idle_mode, length_of_audio, blink_every],
-        outputs=[gen_video],
-    )
-
-    with gr.Row():
-        gr.Examples(examples=get_examples(), inputs=[source_image, driven_audio, preprocess_type, is_still_mode, enhancer],
-                    outputs=[gen_video], fn=generate_video)
-
-demo.launch(debug=True)
+                                label="batch size in generation", step=1, maximum=10, value=2
+                            )
+                            enhancer = gr.Checkbox(label="GFPGAN as Face enhancer")
+                            submit = gr.Button("Generate", elem_id="sadtalker_generate", variant="primary")
+
+            with gr.Tabs(elem_id="sadtalker_genearted"):
+                gen_video = gr.Video(label="Generated video", format="mp4", style="width: 256px")
+
+        if warpfn:
+            submit.click(
+                warpfn(sad_talker.test),
+                [source_image, driven_audio, preprocess_type, is_still_mode, enhancer, batch_size, size_of_image, pose_style],
+                [gen_video],
+            )
+        else:
+            submit.click(
+                sad_talker.test,
+                [source_image, driven_audio, preprocess_type, is_still_mode, enhancer, batch_size, size_of_image, pose_style],
+                [gen_video],
+            )
+
+    return sadtalker_interface
+
+if __name__ == "__main__":
+    demo = sadtalker_demo()
+    demo.queue()
+    demo.launch()