Update app.py

app.py

@@ -1,546 +1,546 @@
-import spaces
-from huggingface_hub import snapshot_download, hf_hub_download
-import os
-import subprocess
-import importlib, site
-from PIL import Image
-import uuid
-import shutil
-import time
-import cv2
-from generate import generate, load_model
-import json
-
-# Re-discover all .pth/.egg-link files
-for sitedir in site.getsitepackages():
-    site.addsitedir(sitedir)
-
-# Clear caches so importlib will pick up new modules
-importlib.invalidate_caches()
-
-def sh(cmd): subprocess.check_call(cmd, shell=True)
-
-try:
-    print("Attempting to download and build sam2...")
-
-    print("download sam")
-    sam_dir = snapshot_download(repo_id="alexnasa/sam2")
-
-    @spaces.GPU(duration=450)
-    def install_sam():
-        os.environ["TORCH_CUDA_ARCH_LIST"] = "9.0"
-        sh(f"cd {sam_dir} && python setup.py build_ext --inplace && pip install -e .")
-
-    print("install sam")
-    install_sam()
-
-    # tell Python to re-scan site-packages now that the egg-link exists
-    import importlib, site; site.addsitedir(site.getsitepackages()[0]); importlib.invalidate_caches()
-
-    flash_attention_installed = True
-    print("sam2 installed successfully.")
-
-except Exception as e:
-    print(f"⚠️ Could not install sam2: {e}")
-    print("Continuing without sam2...")
-
-import torch
-print(f"Torch version: {torch.__version__}")
-
-os.environ["PROCESSED_RESULTS"] = f"{os.getcwd()}/processed_results"
-
-import gradio as gr
-
-
-snapshot_download(repo_id="Wan-AI/Wan2.2-Animate-14B", local_dir="./Wan2.2-Animate-14B")
-wan_animate = load_model(True)
-
-
-rc_mapping = {
-    "Video → Ref Image" : False,
-    "Video ← Ref Image" : True
-}
-
-
-def preprocess_video(input_video_path, session_id=None):
-    
-    if session_id is None:
-        session_id = uuid.uuid4().hex
-
-    output_dir = os.path.join(os.environ["PROCESSED_RESULTS"], session_id)
-    os.makedirs(output_dir, exist_ok=True)
-
-    process_video_path = os.path.join(output_dir, 'input_video.mp4')
-
-    convert_video_to_30fps_and_clip(input_video_path, process_video_path, crop_width=720, crop_height=1280)
-
-    return process_video_path
-
-def extract_audio_from_video_ffmpeg(video_path, output_wav_path, sample_rate=None):
-    """
-    Extracts the audio track from a video file and saves it as a WAV file.
-
-    Args:
-        video_path (str): Path to the input video file.
-        output_wav_path (str): Path to save the extracted WAV file.
-        sample_rate (int, optional): Output sample rate (e.g., 16000). 
-                                     If None, keep the original.
-    """
-    cmd = [
-        'ffmpeg',
-        '-i', video_path,             # Input video
-        '-vn',                        # Disable video
-        '-acodec', 'pcm_s16le',       # 16-bit PCM (WAV format)
-        '-ac', '1',                   # Mono channel (use '2' for stereo)
-        '-y',                         # Overwrite output
-        '-loglevel', 'error'          # Cleaner output
-    ]
-
-    # Only add the sample rate option if explicitly specified
-    if sample_rate is not None:
-        cmd.extend(['-ar', str(sample_rate)])
-
-    cmd.append(output_wav_path)
-    
-    try:
-        subprocess.run(cmd, check=True, capture_output=True, text=True)
-    except subprocess.CalledProcessError as e:
-        raise RuntimeError(f"ffmpeg failed ({e.returncode}): {e.stderr.strip()}")
-
-    
-def combine_video_and_audio_ffmpeg(video_path, audio_path, output_video_path):
-    """
-    Combines a silent MP4 video with a WAV audio file into a single MP4 with sound.
-
-    Args:
-        video_path (str): Path to the silent video file.
-        audio_path (str): Path to the WAV audio file.
-        output_video_path (str): Path to save the output MP4 with audio.
-    """
-    cmd = [
-        'ffmpeg',
-        '-i', video_path,            # Input video
-        '-i', audio_path,            # Input audio
-        '-c:v', 'copy',              # Copy video without re-encoding
-        '-c:a', 'aac',               # Encode audio as AAC (MP4-compatible)
-        '-shortest',                 # Stop when the shortest stream ends
-        '-y',                        # Overwrite output
-        '-loglevel', 'error',
-        output_video_path
-    ]
-    
-    try:
-        subprocess.run(cmd, check=True, capture_output=True, text=True)
-    except subprocess.CalledProcessError as e:
-        raise RuntimeError(f"ffmpeg failed ({e.returncode}): {e.stderr.strip()}")
-
-
-def convert_video_to_30fps_and_clip(
-    input_video_path,
-    output_video_path,
-    duration_s=2,
-    target_fps=30,
-    crop_width=None,
-    crop_height=None
-):
-    # Get input video dimensions using ffprobe
-    if crop_width and crop_height:
-        probe_cmd = [
-            'ffprobe', '-v', 'error', '-select_streams', 'v:0',
-            '-show_entries', 'stream=width,height',
-            '-of', 'json', input_video_path
-        ]
-        probe_result = subprocess.run(probe_cmd, capture_output=True, text=True, check=True)
-        video_info = json.loads(probe_result.stdout)
-        w = video_info['streams'][0]['width']
-        h = video_info['streams'][0]['height']
-
-        # Clamp crop size to not exceed actual dimensions
-        crop_width = min(crop_width, w)
-        crop_height = min(crop_height, h)
-
-        # Center crop offsets
-        crop_x = max((w - crop_width) // 2, 0)
-        crop_y = max((h - crop_height) // 2, 0)
-        crop_filter = f"crop={crop_width}:{crop_height}:{crop_x}:{crop_y}"
-    else:
-        crop_filter = None
-
-    cmd = [
-        'ffmpeg',
-        '-i', input_video_path,
-        '-r', str(target_fps),
-        '-t', str(duration_s),
-    ]
-
-    if crop_filter:
-        cmd += ['-vf', crop_filter]
-
-    cmd += [
-        '-c:v', 'libx264',
-        '-c:a', 'aac',
-        '-strict', 'experimental',
-        '-y',
-        '-loglevel', 'error',
-        output_video_path
-    ]
-
-    try:
-        subprocess.run(cmd, check=True, capture_output=True, text=True)
-    except subprocess.CalledProcessError as e:
-        raise RuntimeError(f"ffmpeg failed ({e.returncode}): {e.stderr.strip()}")
-
-def get_frames_count(video_file):
-
-    # Get video information
-    cap = cv2.VideoCapture(video_file)
-    if not cap.isOpened():
-        error_msg = "Cannot open video file"
-        gr.Warning(error_msg)
-    
-    orig_frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-    orig_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-    orig_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-    
-    cap.release()
-
-    return orig_frame_count
-
-def calculate_time_required(input_video, rc_bool):
-
-    frames_count = get_frames_count(input_video)
-
-    chunks = frames_count // 77 + 1
-
-
-    if rc_bool:
-        pose2d_tracking_duration_s = 75
-        iteration_per_step_s = 13
-    else:
-        pose2d_tracking_duration_s = 50
-        iteration_per_step_s = 12
-        
-    time_required = pose2d_tracking_duration_s + iteration_per_step_s * 20 * chunks
-    print(f'for frames_count:{frames_count} doing {chunks} chunks the time_required is {time_required}')
-    return time_required
-
-def update_time_required(input_video, rc_str):
-
-    if input_video is None:
-        return gr.update(value="⌚ Zero GPU Required: --")
-    
-    rc_bool = rc_mapping[rc_str]
-
-    duration_s = calculate_time_required(input_video, rc_bool)
-    duration_m = duration_s / 60
-    
-    return gr.update(value=f"⌚ Zero GPU Required: ~{duration_s}.0s ({duration_m:.1f} mins)")
-
-def get_duration(input_video, edited_frame, rc_bool, session_id, progress):
-
-    return calculate_time_required(input_video, rc_bool)
-    
-
-@spaces.GPU(duration=get_duration)
-def _animate(input_video, edited_frame, rc_bool, session_id = None, progress=gr.Progress(track_tqdm=True),):
-
-    if session_id is None:
-        session_id = uuid.uuid4().hex
-
-    output_dir = os.path.join(os.environ["PROCESSED_RESULTS"], session_id)
-    os.makedirs(output_dir, exist_ok=True)
-
-    preprocess_dir = os.path.join(output_dir, "preprocess_dir")
-    os.makedirs(preprocess_dir, exist_ok=True)
-
-    output_video_path = os.path.join(output_dir, 'result.mp4')
-
-    # --- Measure preprocess time ---
-    start_preprocess = time.time()
-
-    # w = 720
-    # h = 480
-
-    # w = 720
-    # h = 1280
-
-    w = 480
-    h = 832
-
-    # w = 480
-    # h = 720
-
-    tag_string = "retarget_flag"
-
-    if rc_bool:
-        tag_string = "replace_flag"
-
-    sh("python ./wan/modules/animate/preprocess/preprocess_data.py "
-       "--ckpt_path ./Wan2.2-Animate-14B/process_checkpoint "
-       f"--video_path {input_video} "
-       f"--refer_path {edited_frame} "
-       f"--save_path {preprocess_dir} "
-       f"--resolution_area {w} {h} --{tag_string} "
-       )
-
-    preprocess_time = time.time() - start_preprocess
-    print(f"Preprocess took {preprocess_time:.2f} seconds")
-
-    # --- Measure generate time ---
-    start_generate = time.time()
-    
-    generate(wan_animate, preprocess_dir, output_video_path, rc_bool)
-
-    generate_time = time.time() - start_generate
-    print(f"Generate took {generate_time:.2f} seconds")
-
-    # --- Optional total time ---
-    total_time = preprocess_time + generate_time
-    print(f"Total time: {total_time:.2f} seconds")
-
-    return output_video_path
-
-def animate_scene(input_video, edited_frame, rc_str, session_id = None, progress=gr.Progress(track_tqdm=True),):
-
-    if not input_video:
-        raise gr.Error("Please provide an video")
-    
-    if not edited_frame:
-        raise gr.Error("Please provide an image")
-    
-    if session_id is None:
-        session_id = uuid.uuid4().hex
-
-    rc_bool = rc_mapping[rc_str]
-    
-    output_dir = os.path.join(os.environ["PROCESSED_RESULTS"], session_id)
-    os.makedirs(output_dir, exist_ok=True)
-
-    input_audio_path = os.path.join(output_dir, 'input_audio.wav')
-    
-    extract_audio_from_video_ffmpeg(input_video, input_audio_path)
-
-    output_video_path = _animate(input_video, edited_frame, rc_bool, session_id, progress)
-
-    final_video_path = os.path.join(output_dir, 'final_result.mp4')
-
-    preprocess_dir = os.path.join(output_dir, "preprocess_dir")
-    pose_video =  os.path.join(preprocess_dir, 'src_pose.mp4') 
-
-    if rc_bool:
-        mask_video = os.path.join(preprocess_dir, 'src_mask.mp4')
-        bg_video = os.path.join(preprocess_dir, 'src_bg.mp4')
-        face_video = os.path.join(preprocess_dir, 'src_face.mp4')
-    else:
-        mask_video = os.path.join(preprocess_dir, 'src_pose.mp4') 
-        bg_video = os.path.join(preprocess_dir, 'src_pose.mp4') 
-        face_video = os.path.join(preprocess_dir, 'src_pose.mp4') 
-
-    combine_video_and_audio_ffmpeg(output_video_path, input_audio_path, final_video_path)
-
-    return final_video_path, pose_video, bg_video, mask_video, face_video
-
-css = """
-    #col-container {
-        margin: 0 auto;
-        max-width: 1600px;
-    }
-
-    #step-column {
-        padding: 20px;
-        border-radius: 8px;
-        box-shadow: var(--card-shadow);
-        margin: 10px;
-    }
-
-    #col-showcase {
-        margin: 0 auto;
-        max-width: 1100px;
-    }
-
-    .button-gradient {
-        background: linear-gradient(45deg, rgb(255, 65, 108), rgb(255, 75, 43), rgb(255, 155, 0), rgb(255, 65, 108)) 0% 0% / 400% 400%;
-        border: none;
-        padding: 14px 28px;
-        font-size: 16px;
-        font-weight: bold;
-        color: white;
-        border-radius: 10px;
-        cursor: pointer;
-        transition: 0.3s ease-in-out;
-        animation: 2s linear 0s infinite normal none running gradientAnimation;
-        box-shadow: rgba(255, 65, 108, 0.6) 0px 4px 10px;
-    }
-
-    .toggle-container {
-    display: inline-flex;
-    background-color: #ffd6ff;  /* light pink background */
-    border-radius: 9999px;
-    padding: 4px;
-    position: relative;
-    width: fit-content;
-    font-family: sans-serif;
-    }
-
-    .toggle-container input[type="radio"] {
-    display: none;
-    }
-
-    .toggle-container label {
-    position: relative;
-    z-index: 2;
-    flex: 1;
-    text-align: center;
-    font-weight: 700;
-    color: #4b2ab5; /* dark purple text for unselected */
-    padding: 6px 22px;
-    border-radius: 9999px;
-    cursor: pointer;
-    transition: color 0.25s ease;
-    }
-
-    /* Moving highlight */
-    .toggle-highlight {
-    position: absolute;
-    top: 4px;
-    left: 4px;
-    width: calc(50% - 4px);
-    height: calc(100% - 8px);
-    background-color: #4b2ab5; /* dark purple background */
-    border-radius: 9999px;
-    transition: transform 0.25s ease;
-    z-index: 1;
-    }
-
-    /* When "True" is checked */
-    #true:checked ~ label[for="true"] {
-    color: #ffd6ff; /* light pink text */
-    }
-
-    /* When "False" is checked */
-    #false:checked ~ label[for="false"] {
-    color: #ffd6ff; /* light pink text */
-    }
-
-    /* Move highlight to right side when False is checked */
-    #false:checked ~ .toggle-highlight {
-    transform: translateX(100%);
-    }
-    """
-def start_session(request: gr.Request):
-
-    return request.session_hash
-
-def cleanup(request: gr.Request):
-
-    sid = request.session_hash
-    
-    if sid:
-        d1 = os.path.join(os.environ["PROCESSED_RESULTS"], sid)
-        shutil.rmtree(d1, ignore_errors=True)
-
-with gr.Blocks(css=css, title="Wan 2.2 Animate --replace", theme=gr.themes.Ocean()) as demo:
-        
-    session_state = gr.State()
-    demo.load(start_session, outputs=[session_state])
-
-    with gr.Column(elem_id="col-container"):
-        with gr.Row():
-            gr.HTML(
-                """
-                <div style="text-align: center;">
-                    <p style="font-size:16px; display: inline; margin: 0;">
-                        <strong>Wan2.2-Animate-14B </strong>
-                    </p>
-                    <a href="https://huggingface.co/Wan-AI/Wan2.2-Animate-14B" style="display: inline-block; vertical-align: middle; margin-left: 0.5em;">
-                        [Model]
-                    </a>
-                <div style="text-align: center;">
-                    <p style="font-size:16px; display: inline; margin: 0;">
-                        HF Space By:
-                    </p>
-                    <a href="https://huggingface.co/alexnasa" style="display: inline-block; vertical-align: middle; margin-left: 0.5em;">
-                        <img src="https://img.shields.io/badge/🤗-Follow Me-yellow.svg">
-                    </a>
-                </div>
-                """
-            )
-        with gr.Row():
-            with gr.Column(elem_id="step-column"):
-                gr.HTML("""
-                <div>
-                    <span style="font-size: 24px;">1. Upload a Video</span><br>
-                </div>
-                """)
-                input_video = gr.Video(label="Input Video", height=512)
-
-
-            with gr.Column(elem_id="step-column"):
-                gr.HTML("""
-                <div>
-                    <span style="font-size: 24px;">2. Upload a Ref Image</span><br>
-                </div>
-                """)
-                edited_frame = gr.Image(label="Ref Image", type="filepath", height=512)
-                gr.HTML("""
-                <div>
-                    <span style="font-size: 24px;">3. Choose Mode</span><br>
-                </div>
-                """)
-                replace_character_string = gr.Radio(
-                    ["Video → Ref Image", "Video ← Ref Image"], value="Video → Ref Image", show_label=False
-                )
-
-            with gr.Column(elem_id="step-column"):
-                gr.HTML("""
-                <div>
-                    <span style="font-size: 24px;">4. Wan Animate it!</span><br>
-                </div>
-                """)
-                output_video = gr.Video(label="Edited Video", height=512)
-
-                time_required = gr.Text(value="⌚ Zero GPU Required: --", show_label=False)
-                action_button = gr.Button("Wan Animate 🦆", variant='primary', elem_classes="button-gradient")
-
-                with gr.Accordion("Preprocessed Data", open=False, visible=False):
-                    pose_video = gr.Video(label="Pose Video", height=512)
-                    bg_video = gr.Video(label="Background Video", height=512)
-                    face_video = gr.Video(label="Face Video", height=512)
-                    mask_video = gr.Video(label="Mask Video", height=512)
-
-        with gr.Row():
-            with gr.Column(elem_id="col-showcase"):
-
-                gr.Examples(
-                    examples=[
-
-                        [
-                            "./examples/desi.mp4", 
-                            "./examples/desi.png",     
-                            "Video ← Ref Image"
-                        ],
-
-                        [
-                            "./examples/paul.mp4", 
-                            "./examples/man.png",     
-                            "Video → Ref Image"
-                        ],
-
-
-                    ],
-                    inputs=[input_video, edited_frame, replace_character_string],
-                    outputs=[output_video, pose_video, bg_video, mask_video, face_video],
-                    fn=animate_scene,
-                    cache_examples=True,
-                )
-
-    action_button.click(fn=animate_scene, inputs=[input_video, edited_frame, replace_character_string, session_state], outputs=[output_video, pose_video, bg_video, mask_video, face_video])
-
-    input_video.upload(preprocess_video, inputs=[input_video, session_state], outputs=[input_video]).then(update_time_required, inputs=[input_video, replace_character_string], outputs=[time_required])
-    replace_character_string.change(update_time_required, inputs=[input_video, replace_character_string], outputs=[time_required])
-                   
-if __name__ == "__main__":
-    demo.queue()
-    demo.unload(cleanup)
-    demo.launch(ssr_mode=False, share=True)
+import spaces
+from huggingface_hub import snapshot_download, hf_hub_download
+import os
+import subprocess
+import importlib, site
+from PIL import Image
+import uuid
+import shutil
+import time
+import cv2
+from generate import generate, load_model
+import json
+
+# Re-discover all .pth/.egg-link files
+for sitedir in site.getsitepackages():
+    site.addsitedir(sitedir)
+
+# Clear caches so importlib will pick up new modules
+importlib.invalidate_caches()
+
+def sh(cmd): subprocess.check_call(cmd, shell=True)
+
+try:
+    print("Attempting to download and build sam2...")
+
+    print("download sam")
+    sam_dir = snapshot_download(repo_id="alexnasa/sam2")
+
+    @spaces.GPU(duration=450)
+    def install_sam():
+        os.environ["TORCH_CUDA_ARCH_LIST"] = "9.0"
+        sh(f"cd {sam_dir} && python setup.py build_ext --inplace && pip install -e .")
+
+    print("install sam")
+    install_sam()
+
+    # tell Python to re-scan site-packages now that the egg-link exists
+    import importlib, site; site.addsitedir(site.getsitepackages()[0]); importlib.invalidate_caches()
+
+    flash_attention_installed = True
+    print("sam2 installed successfully.")
+
+except Exception as e:
+    print(f"⚠️ Could not install sam2: {e}")
+    print("Continuing without sam2...")
+
+import torch
+print(f"Torch version: {torch.__version__}")
+
+os.environ["PROCESSED_RESULTS"] = f"{os.getcwd()}/processed_results"
+
+import gradio as gr
+
+
+snapshot_download(repo_id="Wan-AI/Wan2.2-Animate-14B", local_dir="./Wan2.2-Animate-14B")
+wan_animate = load_model(True)
+
+
+rc_mapping = {
+    "Video → Ref Image" : False,
+    "Video ← Ref Image" : True
+}
+
+
+def preprocess_video(input_video_path, session_id=None):
+    
+    if session_id is None:
+        session_id = uuid.uuid4().hex
+
+    output_dir = os.path.join(os.environ["PROCESSED_RESULTS"], session_id)
+    os.makedirs(output_dir, exist_ok=True)
+
+    process_video_path = os.path.join(output_dir, 'input_video.mp4')
+
+    convert_video_to_30fps_and_clip(input_video_path, process_video_path, crop_width=720, crop_height=1280)
+
+    return process_video_path
+
+def extract_audio_from_video_ffmpeg(video_path, output_wav_path, sample_rate=None):
+    """
+    Extracts the audio track from a video file and saves it as a WAV file.
+
+    Args:
+        video_path (str): Path to the input video file.
+        output_wav_path (str): Path to save the extracted WAV file.
+        sample_rate (int, optional): Output sample rate (e.g., 16000). 
+                                     If None, keep the original.
+    """
+    cmd = [
+        'ffmpeg',
+        '-i', video_path,             # Input video
+        '-vn',                        # Disable video
+        '-acodec', 'pcm_s16le',       # 16-bit PCM (WAV format)
+        '-ac', '1',                   # Mono channel (use '2' for stereo)
+        '-y',                         # Overwrite output
+        '-loglevel', 'error'          # Cleaner output
+    ]
+
+    # Only add the sample rate option if explicitly specified
+    if sample_rate is not None:
+        cmd.extend(['-ar', str(sample_rate)])
+
+    cmd.append(output_wav_path)
+    
+    try:
+        subprocess.run(cmd, check=True, capture_output=True, text=True)
+    except subprocess.CalledProcessError as e:
+        raise RuntimeError(f"ffmpeg failed ({e.returncode}): {e.stderr.strip()}")
+
+    
+def combine_video_and_audio_ffmpeg(video_path, audio_path, output_video_path):
+    """
+    Combines a silent MP4 video with a WAV audio file into a single MP4 with sound.
+
+    Args:
+        video_path (str): Path to the silent video file.
+        audio_path (str): Path to the WAV audio file.
+        output_video_path (str): Path to save the output MP4 with audio.
+    """
+    cmd = [
+        'ffmpeg',
+        '-i', video_path,            # Input video
+        '-i', audio_path,            # Input audio
+        '-c:v', 'copy',              # Copy video without re-encoding
+        '-c:a', 'aac',               # Encode audio as AAC (MP4-compatible)
+        '-shortest',                 # Stop when the shortest stream ends
+        '-y',                        # Overwrite output
+        '-loglevel', 'error',
+        output_video_path
+    ]
+    
+    try:
+        subprocess.run(cmd, check=True, capture_output=True, text=True)
+    except subprocess.CalledProcessError as e:
+        raise RuntimeError(f"ffmpeg failed ({e.returncode}): {e.stderr.strip()}")
+
+
+def convert_video_to_30fps_and_clip(
+    input_video_path,
+    output_video_path,
+    duration_s=2,
+    target_fps=30,
+    crop_width=None,
+    crop_height=None
+):
+    # Get input video dimensions using ffprobe
+    if crop_width and crop_height:
+        probe_cmd = [
+            'ffprobe', '-v', 'error', '-select_streams', 'v:0',
+            '-show_entries', 'stream=width,height',
+            '-of', 'json', input_video_path
+        ]
+        probe_result = subprocess.run(probe_cmd, capture_output=True, text=True, check=True)
+        video_info = json.loads(probe_result.stdout)
+        w = video_info['streams'][0]['width']
+        h = video_info['streams'][0]['height']
+
+        # Clamp crop size to not exceed actual dimensions
+        crop_width = min(crop_width, w)
+        crop_height = min(crop_height, h)
+
+        # Center crop offsets
+        crop_x = max((w - crop_width) // 2, 0)
+        crop_y = max((h - crop_height) // 2, 0)
+        crop_filter = f"crop={crop_width}:{crop_height}:{crop_x}:{crop_y}"
+    else:
+        crop_filter = None
+
+    cmd = [
+        'ffmpeg',
+        '-i', input_video_path,
+        '-r', str(target_fps),
+        '-t', str(duration_s),
+    ]
+
+    if crop_filter:
+        cmd += ['-vf', crop_filter]
+
+    cmd += [
+        '-c:v', 'libx264',
+        '-c:a', 'aac',
+        '-strict', 'experimental',
+        '-y',
+        '-loglevel', 'error',
+        output_video_path
+    ]
+
+    try:
+        subprocess.run(cmd, check=True, capture_output=True, text=True)
+    except subprocess.CalledProcessError as e:
+        raise RuntimeError(f"ffmpeg failed ({e.returncode}): {e.stderr.strip()}")
+
+def get_frames_count(video_file):
+
+    # Get video information
+    cap = cv2.VideoCapture(video_file)
+    if not cap.isOpened():
+        error_msg = "Cannot open video file"
+        gr.Warning(error_msg)
+    
+    orig_frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+    orig_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    orig_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    
+    cap.release()
+
+    return orig_frame_count
+
+def calculate_time_required(input_video, rc_bool):
+
+    frames_count = get_frames_count(input_video)
+
+    chunks = frames_count // 77 + 1
+
+
+    if rc_bool:
+        pose2d_tracking_duration_s = 75
+        iteration_per_step_s = 13
+    else:
+        pose2d_tracking_duration_s = 50
+        iteration_per_step_s = 12
+        
+    time_required = pose2d_tracking_duration_s + iteration_per_step_s * 20 * chunks
+    print(f'for frames_count:{frames_count} doing {chunks} chunks the time_required is {time_required}')
+    return time_required
+
+def update_time_required(input_video, rc_str):
+
+    if input_video is None:
+        return gr.update(value="⌚ Zero GPU Required: --")
+    
+    rc_bool = rc_mapping[rc_str]
+
+    duration_s = calculate_time_required(input_video, rc_bool)
+    duration_m = duration_s / 60
+    
+    return gr.update(value=f"⌚ Zero GPU Required: ~{duration_s}.0s ({duration_m:.1f} mins)")
+
+def get_duration(input_video, edited_frame, rc_bool, session_id, progress):
+
+    return calculate_time_required(input_video, rc_bool)
+    
+
+@spaces.GPU(duration=get_duration)
+def _animate(input_video, edited_frame, rc_bool, session_id = None, progress=gr.Progress(track_tqdm=True),):
+
+    if session_id is None:
+        session_id = uuid.uuid4().hex
+
+    output_dir = os.path.join(os.environ["PROCESSED_RESULTS"], session_id)
+    os.makedirs(output_dir, exist_ok=True)
+
+    preprocess_dir = os.path.join(output_dir, "preprocess_dir")
+    os.makedirs(preprocess_dir, exist_ok=True)
+
+    output_video_path = os.path.join(output_dir, 'result.mp4')
+
+    # --- Measure preprocess time ---
+    start_preprocess = time.time()
+
+    # w = 720
+    # h = 480
+
+    # w = 720
+    # h = 1280
+
+    w = 480
+    h = 832
+
+    # w = 480
+    # h = 720
+
+    tag_string = "retarget_flag"
+
+    if rc_bool:
+        tag_string = "replace_flag"
+
+    sh("python ./wan/modules/animate/preprocess/preprocess_data.py "
+       "--ckpt_path ./Wan2.2-Animate-14B/process_checkpoint "
+       f"--video_path {input_video} "
+       f"--refer_path {edited_frame} "
+       f"--save_path {preprocess_dir} "
+       f"--resolution_area {w} {h} --{tag_string} "
+       )
+
+    preprocess_time = time.time() - start_preprocess
+    print(f"Preprocess took {preprocess_time:.2f} seconds")
+
+    # --- Measure generate time ---
+    start_generate = time.time()
+    
+    generate(wan_animate, preprocess_dir, output_video_path, rc_bool)
+
+    generate_time = time.time() - start_generate
+    print(f"Generate took {generate_time:.2f} seconds")
+
+    # --- Optional total time ---
+    total_time = preprocess_time + generate_time
+    print(f"Total time: {total_time:.2f} seconds")
+
+    return output_video_path
+
+def animate_scene(input_video, edited_frame, rc_str, session_id = None, progress=gr.Progress(track_tqdm=True),):
+
+    if not input_video:
+        raise gr.Error("Please provide an video")
+    
+    if not edited_frame:
+        raise gr.Error("Please provide an image")
+    
+    if session_id is None:
+        session_id = uuid.uuid4().hex
+
+    rc_bool = rc_mapping[rc_str]
+    
+    output_dir = os.path.join(os.environ["PROCESSED_RESULTS"], session_id)
+    os.makedirs(output_dir, exist_ok=True)
+
+    input_audio_path = os.path.join(output_dir, 'input_audio.wav')
+    
+    extract_audio_from_video_ffmpeg(input_video, input_audio_path)
+
+    output_video_path = _animate(input_video, edited_frame, rc_bool, session_id, progress)
+
+    final_video_path = os.path.join(output_dir, 'final_result.mp4')
+
+    preprocess_dir = os.path.join(output_dir, "preprocess_dir")
+    pose_video =  os.path.join(preprocess_dir, 'src_pose.mp4') 
+
+    if rc_bool:
+        mask_video = os.path.join(preprocess_dir, 'src_mask.mp4')
+        bg_video = os.path.join(preprocess_dir, 'src_bg.mp4')
+        face_video = os.path.join(preprocess_dir, 'src_face.mp4')
+    else:
+        mask_video = os.path.join(preprocess_dir, 'src_pose.mp4') 
+        bg_video = os.path.join(preprocess_dir, 'src_pose.mp4') 
+        face_video = os.path.join(preprocess_dir, 'src_pose.mp4') 
+
+    combine_video_and_audio_ffmpeg(output_video_path, input_audio_path, final_video_path)
+
+    return final_video_path, pose_video, bg_video, mask_video, face_video
+
+css = """
+    #col-container {
+        margin: 0 auto;
+        max-width: 1600px;
+    }
+
+    #step-column {
+        padding: 20px;
+        border-radius: 8px;
+        box-shadow: var(--card-shadow);
+        margin: 10px;
+    }
+
+    #col-showcase {
+        margin: 0 auto;
+        max-width: 1100px;
+    }
+
+    .button-gradient {
+        background: linear-gradient(45deg, rgb(255, 65, 108), rgb(255, 75, 43), rgb(255, 155, 0), rgb(255, 65, 108)) 0% 0% / 400% 400%;
+        border: none;
+        padding: 14px 28px;
+        font-size: 16px;
+        font-weight: bold;
+        color: white;
+        border-radius: 10px;
+        cursor: pointer;
+        transition: 0.3s ease-in-out;
+        animation: 2s linear 0s infinite normal none running gradientAnimation;
+        box-shadow: rgba(255, 65, 108, 0.6) 0px 4px 10px;
+    }
+
+    .toggle-container {
+    display: inline-flex;
+    background-color: #ffd6ff;  /* light pink background */
+    border-radius: 9999px;
+    padding: 4px;
+    position: relative;
+    width: fit-content;
+    font-family: sans-serif;
+    }
+
+    .toggle-container input[type="radio"] {
+    display: none;
+    }
+
+    .toggle-container label {
+    position: relative;
+    z-index: 2;
+    flex: 1;
+    text-align: center;
+    font-weight: 700;
+    color: #4b2ab5; /* dark purple text for unselected */
+    padding: 6px 22px;
+    border-radius: 9999px;
+    cursor: pointer;
+    transition: color 0.25s ease;
+    }
+
+    /* Moving highlight */
+    .toggle-highlight {
+    position: absolute;
+    top: 4px;
+    left: 4px;
+    width: calc(50% - 4px);
+    height: calc(100% - 8px);
+    background-color: #4b2ab5; /* dark purple background */
+    border-radius: 9999px;
+    transition: transform 0.25s ease;
+    z-index: 1;
+    }
+
+    /* When "True" is checked */
+    #true:checked ~ label[for="true"] {
+    color: #ffd6ff; /* light pink text */
+    }
+
+    /* When "False" is checked */
+    #false:checked ~ label[for="false"] {
+    color: #ffd6ff; /* light pink text */
+    }
+
+    /* Move highlight to right side when False is checked */
+    #false:checked ~ .toggle-highlight {
+    transform: translateX(100%);
+    }
+    """
+def start_session(request: gr.Request):
+
+    return request.session_hash
+
+def cleanup(request: gr.Request):
+
+    sid = request.session_hash
+    
+    if sid:
+        d1 = os.path.join(os.environ["PROCESSED_RESULTS"], sid)
+        shutil.rmtree(d1, ignore_errors=True)
+
+with gr.Blocks(css=css, title="Wan 2.2 Animate --replace", theme=gr.themes.Ocean()) as demo:
+        
+    session_state = gr.State()
+    demo.load(start_session, outputs=[session_state])
+
+    with gr.Column(elem_id="col-container"):
+        with gr.Row():
+            gr.HTML(
+                """
+                <div style="text-align: center;">
+                    <p style="font-size:16px; display: inline; margin: 0;">
+                        <strong>Wan2.2-Animate-14B </strong>
+                    </p>
+                    <a href="https://huggingface.co/Wan-AI/Wan2.2-Animate-14B" style="display: inline-block; vertical-align: middle; margin-left: 0.5em;">
+                        [Model]
+                    </a>
+                <div style="text-align: center;">
+                    <p style="font-size:16px; display: inline; margin: 0;">
+                        HF Space By:
+                    </p>
+                    <a href="https://huggingface.co/alexnasa" style="display: inline-block; vertical-align: middle; margin-left: 0.5em;">
+                        <img src="https://img.shields.io/badge/🤗-Follow Me-yellow.svg">
+                    </a>
+                </div>
+                """
+            )
+        with gr.Row():
+            with gr.Column(elem_id="step-column"):
+                gr.HTML("""
+                <div>
+                    <span style="font-size: 24px;">1. Upload a Video</span><br>
+                </div>
+                """)
+                input_video = gr.Video(label="Input Video", height=512)
+
+
+            with gr.Column(elem_id="step-column"):
+                gr.HTML("""
+                <div>
+                    <span style="font-size: 24px;">2. Upload a Ref Image</span><br>
+                </div>
+                """)
+                edited_frame = gr.Image(label="Ref Image", type="filepath", height=512)
+                gr.HTML("""
+                <div>
+                    <span style="font-size: 24px;">3. Choose Mode</span><br>
+                </div>
+                """)
+                replace_character_string = gr.Radio(
+                    ["Video → Ref Image", "Video ← Ref Image"], value="Video → Ref Image", show_label=False
+                )
+
+            with gr.Column(elem_id="step-column"):
+                gr.HTML("""
+                <div>
+                    <span style="font-size: 24px;">4. Wan Animate it!</span><br>
+                </div>
+                """)
+                output_video = gr.Video(label="Edited Video", height=512)
+
+                time_required = gr.Text(value="⌚ Zero GPU Required: --", show_label=False)
+                action_button = gr.Button("Wan Animate 🦆", variant='primary', elem_classes="button-gradient")
+
+                with gr.Accordion("Preprocessed Data", open=False, visible=False):
+                    pose_video = gr.Video(label="Pose Video", height=512)
+                    bg_video = gr.Video(label="Background Video", height=512)
+                    face_video = gr.Video(label="Face Video", height=512)
+                    mask_video = gr.Video(label="Mask Video", height=512)
+
+        with gr.Row():
+            with gr.Column(elem_id="col-showcase"):
+
+                gr.Examples(
+                    examples=[
+
+                        [
+                            "./examples/desi.mp4", 
+                            "./examples/desi.png",     
+                            "Video → Ref Image"
+                        ],
+
+                        [
+                            "./examples/paul.mp4", 
+                            "./examples/man.png",      
+                            "Video ← Ref Image"
+                        ],
+
+
+                    ],
+                    inputs=[input_video, edited_frame, replace_character_string],
+                    outputs=[output_video, pose_video, bg_video, mask_video, face_video],
+                    fn=animate_scene,
+                    cache_examples=True,
+                )
+
+    action_button.click(fn=animate_scene, inputs=[input_video, edited_frame, replace_character_string, session_state], outputs=[output_video, pose_video, bg_video, mask_video, face_video])
+
+    input_video.upload(preprocess_video, inputs=[input_video, session_state], outputs=[input_video]).then(update_time_required, inputs=[input_video, replace_character_string], outputs=[time_required])
+    replace_character_string.change(update_time_required, inputs=[input_video, replace_character_string], outputs=[time_required])
+                   
+if __name__ == "__main__":
+    demo.queue()
+    demo.unload(cleanup)
+    demo.launch(ssr_mode=False, share=True)