Spaces:
Running
on
A10G
Running
on
A10G
File size: 8,055 Bytes
db12400 b127fd6 5e44253 6770682 5e44253 3c5c831 19e4624 4382d6d 19e4624 3c5c831 19e4624 25b5212 19e4624 ed63de9 3c5c831 d489594 3c5c831 2bbacca 3c5c831 eef129e db12400 c3d5a7d 5e44253 b8efd0d c292509 6770682 7bb51ba c512cd9 b8efd0d 5e44253 0e2a0ec 5e44253 c512cd9 6770682 5e44253 6770682 5e44253 c512cd9 5e44253 54d06ee c512cd9 55c9cad 5e44253 3e4418e 6770682 936c431 0e2a0ec 936c431 6770682 5e44253 c8537f5 6770682 936c431 7bd3e7e 86d0d5f 5089f52 4893b9a 25b5212 fb90370 25b5212 5e44253 c512cd9 6770682 db12400 b8efd0d deb0f32 b8efd0d 4577161 b8efd0d 9e2421a b8efd0d 6a04784 e38439c deb0f32 bde38a0 54d06ee 19e4624 0880cda 7fa6f4c bde38a0 19e4624 415663b cb9800b 604385b 6a04784 6770682 f3f522f bb8add2 4bb0209 f3f522f b8efd0d 6770682 f90f58c 6770682 db12400 f3f522f deb0f32 b3003aa |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 |
import gradio as gr
import os
import cv2
import numpy as np
from moviepy.editor import *
from share_btn import community_icon_html, loading_icon_html, share_js
from diffusers import StableDiffusionInstructPix2PixPipeline
import torch
from PIL import Image, ImageOps
import time
import psutil
import math
import random
pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained("timbrooks/instruct-pix2pix", torch_dtype=torch.float16, safety_checker=None)
device = "GPU π₯" if torch.cuda.is_available() else "CPU π₯Ά"
if torch.cuda.is_available():
pipe = pipe.to("cuda")
def pix2pix(
input_image: Image.Image,
instruction: str,
steps: int,
seed: int,
text_cfg_scale: float,
image_cfg_scale: float,
):
width, height = input_image.size
factor = 512 / max(width, height)
factor = math.ceil(min(width, height) * factor / 64) * 64 / min(width, height)
width = int((width * factor) // 64) * 64
height = int((height * factor) // 64) * 64
input_image = ImageOps.fit(input_image, (width, height), method=Image.Resampling.LANCZOS)
if instruction == "":
return [input_image, seed]
generator = torch.manual_seed(seed)
edited_image = pipe(
instruction, image=input_image,
guidance_scale=text_cfg_scale, image_guidance_scale=image_cfg_scale,
num_inference_steps=steps, generator=generator,
).images[0]
print(f"EDITED: {edited_image}")
return edited_image
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, seed_in, trim_value):
print(prompt)
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)
result_frames = []
print("set stop frames to: " + str(n_frame))
for i in frames_list[0:int(n_frame)]:
pil_i = Image.open(i).convert("RGB")
pix2pix_img = pix2pix(pil_i, prompt, 50, seed_in, 7.5, 1.5)
print(pix2pix_img)
image = Image.open(pix2pix_img)
rgb_im = image.convert("RGB")
# exporting the image
rgb_im.save(f"result_img-{i}.jpg")
result_frames.append(f"result_img-{i}.jpg")
print("frame " + i + "/" + str(n_frame) + ": done;")
final_vid = create_video(result_frames, fps)
print("finished !")
return final_vid, gr.Group.update(visible=True)
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;">
Pix2Pix Video
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
Apply Instruct Pix2Pix Diffusion to a video
</p>
</div>
"""
article = """
<div class="footer">
<p>
Examples by <a href="https://twitter.com/CitizenPlain" target="_blank">Nathan Shipley</a> β’
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")
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():
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,seed_inp, trim_in]
outputs = [video_out, share_group]
#ex = gr.Examples(
# [
# ["Make it a marble sculpture", "./examples/pexels-jill-burrow-7665249_512x512.mp4", 422112651, 4],
# ["Make it molten lava", "./examples/Ocean_Pexels_ 8953474_512x512.mp4", 43571876, 4]
# ],
# inputs=inputs,
# outputs=outputs,
# fn=infer,
# cache_examples=True,
#)
gr.HTML(article)
submit_btn.click(infer, inputs, outputs)
share_button.click(None, [], [], _js=share_js)
demo.queue(max_size=12).launch()
|