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from __future__ import annotations
import gradio as gr
import os
import cv2
import numpy as np
from PIL import Image
from moviepy.editor import *
from share_btn import community_icon_html, loading_icon_html, share_js
import pathlib
import shlex
import subprocess
if os.getenv('SYSTEM') == 'spaces':
with open('patch') as f:
subprocess.run(shlex.split('patch -p1'), stdin=f, cwd='ControlNet')
base_url = 'https://huggingface.co/lllyasviel/ControlNet/resolve/main/annotator/ckpts/'
names = [
'body_pose_model.pth',
'dpt_hybrid-midas-501f0c75.pt',
'hand_pose_model.pth',
'mlsd_large_512_fp32.pth',
'mlsd_tiny_512_fp32.pth',
'network-bsds500.pth',
'upernet_global_small.pth',
]
for name in names:
command = f'wget https://huggingface.co/lllyasviel/ControlNet/resolve/main/annotator/ckpts/{name} -O {name}'
out_path = pathlib.Path(f'ControlNet/annotator/ckpts/{name}')
if out_path.exists():
continue
subprocess.run(shlex.split(command), cwd='ControlNet/annotator/ckpts/')
from model import Model
model = Model()
def controlnet(i, prompt, control_task, seed_in):
img= Image.open(i)
np_img = np.array(img)
a_prompt = "best quality, extremely detailed"
n_prompt = "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality"
num_samples = 1
image_resolution = 512
detect_resolution = 512
ddim_steps = 20
scale = 9.0
eta = 0.0
if control_task == 'Canny':
result = model.process_canny(np_img, prompt, a_prompt, n_prompt, num_samples,
image_resolution, detect_resolution, ddim_steps, scale, seed_in, eta)
elif control_task == 'Depth':
result = model.process_depth(np_img, prompt, a_prompt, n_prompt, num_samples,
image_resolution, detect_resolution, ddim_steps, scale, seed_in, eta)
elif control_task == 'Pose':
result = model.process_pose(np_img, prompt, a_prompt, n_prompt, num_samples,
image_resolution, detect_resolution, ddim_steps, scale, seed_in, eta)
#print(result[0])
im = Image.fromarray(result[1])
im.save("your_file" + str(i) + ".jpeg")
return "your_file" + str(i) + ".jpeg"
def get_frames(video_in):
frames = []
#resize the video
clip = VideoFileClip(video_in)
#check fps
if clip.fps > 30:
print("vide rate is over 30, resetting to 30")
clip_resized = clip.resize(height=512)
clip_resized.write_videofile("video_resized.mp4", fps=30)
else:
print("video rate is OK")
clip_resized = clip.resize(height=512)
clip_resized.write_videofile("video_resized.mp4", fps=clip.fps)
print("video resized to 512 height")
# Opens the Video file with CV2
cap= cv2.VideoCapture("video_resized.mp4")
fps = cap.get(cv2.CAP_PROP_FPS)
print("video fps: " + str(fps))
i=0
while(cap.isOpened()):
ret, frame = cap.read()
if ret == False:
break
cv2.imwrite('kang'+str(i)+'.jpg',frame)
frames.append('kang'+str(i)+'.jpg')
i+=1
cap.release()
cv2.destroyAllWindows()
print("broke the video into frames")
return frames, fps
def create_video(frames, fps):
print("building video result")
clip = ImageSequenceClip(frames, fps=fps)
clip.write_videofile("movie.mp4", fps=fps)
return 'movie.mp4'
def infer(prompt,video_in, control_task, seed_in, trim_value):
print(f"""
βββββββββββββββ
{prompt}
βββββββββββββββ""")
# 1. break video into frames and get FPS
break_vid = get_frames(video_in)
frames_list= break_vid[0]
fps = break_vid[1]
n_frame = int(trim_value*fps)
if n_frame >= len(frames_list):
print("video is shorter than the cut value")
n_frame = len(frames_list)
# 2. prepare frames result array
result_frames = []
print("set stop frames to: " + str(n_frame))
for i in frames_list[0:int(n_frame)]:
controlnet_img = controlnet(i, prompt,control_task, seed_in)
#images = controlnet_img[0]
#rgb_im = images[0].convert("RGB")
# exporting the image
#rgb_im.save(f"result_img-{i}.jpg")
result_frames.append(controlnet_img)
print("frame " + i + "/" + str(n_frame) + ": done;")
final_vid = create_video(result_frames, fps)
print("finished !")
return final_vid, gr.Group.update(visible=True)
#return controlnet_img
title = """
<div style="text-align: center; max-width: 700px; margin: 0 auto;">
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
"
>
<h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
ControlNet Video
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
Apply ControlNet to a video
</p>
</div>
"""
article = """
<div class="footer">
<p>
Follow <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a> for future updates π€
</p>
</div>
<div id="may-like-container" style="display: flex;justify-content: center;flex-direction: column;align-items: center;margin-bottom: 30px;">
<p>You may also like: </p>
<div id="may-like-content" style="display:flex;flex-wrap: wrap;align-items:center;height:20px;">
<svg height="20" width="162" style="margin-left:4px;margin-bottom: 6px;">
<a href="https://huggingface.co/spaces/timbrooks/instruct-pix2pix" target="_blank">
<image href="https://img.shields.io/badge/π€ Spaces-Instruct_Pix2Pix-blue" src="https://img.shields.io/badge/π€ Spaces-Instruct_Pix2Pix-blue.png" height="20"/>
</a>
</svg>
</div>
</div>
"""
with gr.Blocks(css='style.css') as demo:
with gr.Column(elem_id="col-container"):
gr.HTML(title)
with gr.Row():
with gr.Column():
video_inp = gr.Video(label="Video source", source="upload", type="filepath", elem_id="input-vid")
prompt = gr.Textbox(label="Prompt", placeholder="enter prompt", show_label=False, elem_id="prompt-in")
control_task = gr.Dropdown(["Canny", "Depth", "Pose"], value=["Pose"], multiselect=False),
with gr.Row():
seed_inp = gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1, value=123456)
trim_in = gr.Slider(label="Cut video at (s)", minimun=1, maximum=5, step=1, value=1)
with gr.Column():
#status = gr.Textbox()
video_out = gr.Video(label="Pix2pix video result", elem_id="video-output")
gr.HTML("""
<a style="display:inline-block" href="https://huggingface.co/spaces/fffiloni/Pix2Pix-Video?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a>
work with longer videos / skip the queue:
""", elem_id="duplicate-container")
submit_btn = gr.Button("Generate Pix2Pix video")
with gr.Group(elem_id="share-btn-container", visible=False) as share_group:
community_icon = gr.HTML(community_icon_html)
loading_icon = gr.HTML(loading_icon_html)
share_button = gr.Button("Share to community", elem_id="share-btn")
inputs = [prompt,video_inp,control_task, seed_inp, trim_in]
outputs = [video_out, share_group]
#outputs = [status]
gr.HTML(article)
submit_btn.click(infer, inputs, outputs)
share_button.click(None, [], [], _js=share_js)
demo.launch().queue(max_size=12) |