Spaces:
Running
on
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Running
on
Zero
File size: 4,338 Bytes
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import gradio as gr
from loadimg import load_img
import spaces
from transformers import AutoModelForImageSegmentation
import torch
from torchvision import transforms
import moviepy.editor as mp
from pydub import AudioSegment
from PIL import Image
import numpy as np
import os
import tempfile
import uuid
torch.set_float32_matmul_precision(["high", "highest"][0])
birefnet = AutoModelForImageSegmentation.from_pretrained(
"ZhengPeng7/BiRefNet", trust_remote_code=True
)
birefnet.to("cuda")
transform_image = transforms.Compose(
[
transforms.Resize((1024, 1024)),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
]
)
@spaces.GPU
def fn(vid, fps, color, progress=gr.Progress()):
# Load the video using moviepy
video = mp.VideoFileClip(vid)
audio = video.audio
frames = list(video.iter_frames(fps=fps))
total_frames = len(frames)
processed_frames_no_bg = []
processed_frames_changed_bg = []
# Create a live preview state
preview_no_bg = None
preview_with_bg = None
for idx, frame in enumerate(progress.tqdm(frames)):
pil_image = Image.fromarray(frame)
processed_image, mask = process(pil_image, color)
processed_frames_no_bg.append(np.array(processed_image))
background = Image.new("RGBA", pil_image.size, color + (255,))
composed_image = Image.composite(pil_image, background, mask)
processed_frames_changed_bg.append(np.array(composed_image))
# Update preview every 10 frames or on the last frame
if idx % 10 == 0 or idx == total_frames - 1:
preview_no_bg = np.array(processed_image)
preview_with_bg = np.array(composed_image)
yield preview_no_bg, preview_with_bg, None, None
# Create videos from processed frames
temp_dir = "temp"
os.makedirs(temp_dir, exist_ok=True)
processed_video = mp.ImageSequenceClip(processed_frames_changed_bg, fps=fps)
processed_video = processed_video.set_audio(audio)
temp_filepath = os.path.join(temp_dir, f"{uuid.uuid4()}.mp4")
processed_video.write_videofile(temp_filepath, codec="libx264")
processed_video_no_bg = mp.ImageSequenceClip(processed_frames_no_bg, fps=fps)
processed_video_no_bg = processed_video_no_bg.set_audio(audio)
temp_filepath_no_bg = os.path.join(temp_dir, f"{uuid.uuid4()}.webm")
processed_video_no_bg.write_videofile(temp_filepath_no_bg, codec="libvpx")
# Final yield with completed videos
yield None, None, temp_filepath_no_bg, temp_filepath
def process(image, color_hex):
image_size = image.size
input_images = transform_image(image).unsqueeze(0).to("cuda")
with torch.no_grad():
preds = birefnet(input_images)[-1].sigmoid().cpu()
pred = preds[0].squeeze()
pred_pil = transforms.ToPILImage()(pred)
mask = pred_pil.resize(image_size)
color_rgb = tuple(int(color_hex[i:i + 2], 16) for i in (1, 3, 5))
background = Image.new("RGBA", image_size, color_rgb + (255,))
image = Image.composite(image, background, mask)
return image, mask
def change_color(in_video, fps_slider, color_picker):
return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
with gr.Blocks() as demo:
with gr.Row():
in_video = gr.Video(label="Input Video")
no_bg_video = gr.Video(label="No BG Video", visible=True)
out_video = gr.Video(label="Output Video", visible=True)
with gr.Row(visible=False) as preview_row:
preview_no_bg = gr.Image(label="Live Preview (No Background)", visible=True)
preview_with_bg = gr.Image(label="Live Preview (With Background)", visible=True)
with gr.Row():
fps_slider = gr.Slider(minimum=1, maximum=60, step=1, value=12, label="Output FPS")
color_picker = gr.ColorPicker(label="Background Color", value="#00FF00")
submit_button = gr.Button("Change Background")
# Handle visibility changes and processing
submit_button.click(
fn=fn,
inputs=[in_video, fps_slider, color_picker],
outputs=[preview_no_bg, preview_with_bg, no_bg_video, out_video]
)
if __name__ == "__main__":
demo.launch(show_error=True) |