forked from wammjis/Animator
-
Notifications
You must be signed in to change notification settings - Fork 0
/
animation.py
381 lines (306 loc) · 15.6 KB
/
animation.py
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
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
#
# Animation Script v0.7
# Inspired by Deforum Notebook
# Must have ffmpeg installed in path.
# Poor img2img implentation, will trash images that aren't moving.
#
# See https://github.com/Animator-Anon/Animator
import os, time
import modules.scripts as scripts
import gradio as gr
from modules import processing, shared, sd_samplers, images
from modules.processing import Processed, process_images
from modules.sd_samplers import samplers
from modules.shared import opts, cmd_opts, state
import random
import subprocess
import numpy as np
import json
import cv2
import torch
from PIL import Image, ImageFilter, ImageDraw
def zoom_at2(img, x, y, zoom):
w, h = img.size
#Zoom image
img2 = img.resize((int(w*zoom), int(h*zoom)), Image.Resampling.LANCZOS)
#Create background image
padding=2
resimg = addnoise(img.copy(), 0.75).resize((w+padding*2, h+padding*2), Image.Resampling.LANCZOS).\
filter(ImageFilter.GaussianBlur(5)).\
crop((padding,padding,w+padding,h+padding))
resimg.paste(img2, (int((w - img2.size[0])/2 + x),int((h - img2.size[1])/2 + y)))
return resimg
def addnoise(img, percent):
#Draw coloured circles randomly over the image. Lame, but for testing.
#print("Noise function")
w2, h2 = img.size
draw = ImageDraw.Draw(img)
for i in range(int(50*float(percent))):
x2=random.randint(0,w2)
y2=random.randint(0,h2)
s2=random.randint(0,int(50*float(percent)))
pos = (x2, y2, x2 + s2, y2 + s2)
draw.ellipse(pos, fill=(random.randint(0,255), random.randint(0,255), random.randint(0,255)), outline=(0, 0, 0))
return img
def opencvtransform(pil_img, angle, translation_x, translation_y, zoom, wrap):
#Convert PIL to OpenCV2 format.
numpy_image=np.array(pil_img)
prev_img_cv2=cv2.cvtColor(numpy_image, cv2.COLOR_RGB2BGR)
#Set up matrices for transformations
center = (pil_img.size[0] // 2, pil_img.size[1] // 2)
trans_mat = np.float32([[1, 0, translation_x], [0, 1, translation_y]])
rot_mat = cv2.getRotationMatrix2D(center, angle, zoom)
trans_mat = np.vstack([trans_mat, [0,0,1]])
rot_mat = np.vstack([rot_mat, [0,0,1]])
xform = np.matmul(rot_mat, trans_mat)
opencv_image = cv2.warpPerspective(
prev_img_cv2,
xform,
(prev_img_cv2.shape[1], prev_img_cv2.shape[0]),
borderMode=cv2.BORDER_WRAP if wrap else cv2.BORDER_REPLICATE
)
#Convert OpenCV2 image back to PIL
color_coverted = cv2.cvtColor(opencv_image, cv2.COLOR_BGR2RGB)
return Image.fromarray(color_coverted)
def make_gif(filepath, filename, fps, create_vid, create_bat):
#Create filenames
in_filename = f"{str(filename)}_%05d.png"
out_filename = f"{str(filename)}.gif"
#Build cmd for bat output, local file refs only
cmd = [
'ffmpeg',
'-y',
'-r', str(fps),
'-i', in_filename.replace("%","%%"),
out_filename
]
#create bat file
if create_bat:
with open(os.path.join(filepath, "makegif.bat"), "w+", encoding="utf-8") as f:
f.writelines([" ".join(cmd), "\r\n", "pause"])
#Fix paths for normal output
cmd[5]= os.path.join(filepath, in_filename)
cmd[6]= os.path.join(filepath, out_filename)
#create output if requested
if create_vid:
process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
# stdout, stderr = process.communicate()
# if process.returncode != 0:
# print(stderr)
# raise RuntimeError(stderr)
def make_webm(filepath, filename, fps, create_vid, create_bat):
in_filename = f"{str(filename)}_%05d.png"
out_filename = f"{str(filename)}.webm"
cmd = [
'ffmpeg',
'-y',
'-framerate', str(fps),
'-i', in_filename.replace("%","%%"),
'-crf', str(50),
'-preset', 'veryfast',
out_filename
]
if create_bat:
with open(os.path.join(filepath, "makewebm.bat"), "w+", encoding="utf-8") as f:
f.writelines([" ".join(cmd), "\r\n", "pause"])
cmd[5]= os.path.join(filepath, in_filename)
cmd[10]= os.path.join(filepath, out_filename)
if create_vid:
process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
# stdout, stderr = process.communicate()
# if process.returncode != 0:
# print(stderr)
# raise RuntimeError(stderr)
def make_mp4(filepath, filename, fps, create_vid, create_bat):
in_filename = f"{str(filename)}_%05d.png"
out_filename = f"{str(filename)}.mp4"
cmd = [
'ffmpeg',
'-y',
'-r', str(fps),
'-i', in_filename.replace("%","%%"),
'-c:v', 'libx264',
'-vf',
f'fps={fps}',
'-pix_fmt', 'yuv420p',
'-crf', '17',
'-preset', 'veryfast',
out_filename
]
if create_bat:
with open(os.path.join(filepath, "makemp4.bat"), "w+", encoding="utf-8") as f:
f.writelines([" ".join(cmd), "\r\n", "pause"])
cmd[5]= os.path.join(filepath, in_filename)
cmd[16]= os.path.join(filepath, out_filename)
if create_vid:
process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
# stdout, stderr = process.communicate()
# if process.returncode != 0:
# print(stderr)
# raise RuntimeError(stderr)
class Script(scripts.Script):
def title(self):
return "Animator"
def show(self, is_img2img):
return is_img2img
def ui(self, is_img2img):
i1 = gr.HTML("<p style=\"margin-bottom:0.75em\">Render these video formats:</p>")
with gr.Row():
vid_gif = gr.Checkbox(label="GIF", value=False)
vid_mp4 = gr.Checkbox(label="MP4", value=False)
vid_webm = gr.Checkbox(label="WEBM", value=True)
i2 = gr.HTML("<p style=\"margin-bottom:0.75em\">Animation Parameters</p>")
with gr.Row():
totaltime = gr.Textbox(label="Total Animation Length (s)", lines=1, value="10.0")
fps = gr.Textbox(label="Framerate", lines=1, value="15")
with gr.Row():
add_noise = gr.Checkbox(label="Add_Noise", value=False)
noise_strength = gr.Slider(label="Noise Strength", minimum=0.0, maximum=1.0, step=0.01, value=0.10)
with gr.Row():
noise_decay = gr.Checkbox(label="Denoising_Decay", value=False)
decay_rate = gr.Slider(label="Denoising Decay Rate", minimum=0.1, maximum=1.9, step=0.01, value=0.50)
i5 = gr.HTML("<p style=\"margin-bottom:0.75em\">Initial Parameters</p>")
with gr.Row():
denoising_strength = gr.Slider(label="Denoising Strength (overrides img2img slider)", minimum=0.0, maximum=1.0, step=0.01, value=0.40)
with gr.Row():
zoom_factor = gr.Textbox(label="Zoom Factor (scale/s)", lines=1, value="1.0")
x_shift = gr.Textbox(label="X Pixel Shift (pixels/s)", lines=1, value="0")
y_shift = gr.Textbox(label="Y Pixel Shift (pixels/s)", lines=1, value="0")
i3 = gr.HTML("<p style=\"margin-bottom:0.75em\">Prompt Template, applied to each keyframe below</p>")
tmpl_pos = gr.Textbox(label="Positive Prompts", lines=1, value="")
tmpl_neg = gr.Textbox(label="Negative Prompts", lines=1, value="")
i4 = gr.HTML("<p style=\"margin-bottom:0.75em\">Keyframe Format: <br>Time (s) | Desnoise | Zoom (/s) | X Shift (pix/s) | Y shift (pix/s) | Positive Prompts | Negative Prompts | Seed</p>")
prompts = gr.Textbox(label="Keyframes:", lines=5, value="")
return [i1, i2, i3, i4, totaltime, fps, vid_gif, vid_mp4, vid_webm, zoom_factor, tmpl_pos, tmpl_neg, prompts, denoising_strength, x_shift, y_shift, noise_decay, add_noise, noise_strength, decay_rate]
def run(self, p, i1, i2, i3, i4, totaltime, fps, vid_gif, vid_mp4, vid_webm, zoom_factor, tmpl_pos, tmpl_neg, prompts, denoising_strength, x_shift, y_shift, noise_decay, add_noise, noise_strength,decay_rate):
outfilename = time.strftime('%Y%m%d%H%M%S')
outpath = os.path.join(p.outpath_samples, outfilename)
if not os.path.exists(outpath):
os.mkdir(outpath)
p.do_not_save_samples = True
p.do_not_save_grid = True
#Build prompt dict of tuples.
# format of myprompts[framenumber]=("positive prompt","negative prompt")
myprompts={}
for myline in prompts.splitlines():
lineparts = myline.split("|")
if len(lineparts) < 8:
continue
tmpframe = int(float(lineparts[0]) * int(fps))
myprompts[tmpframe] = (lineparts[1].strip(),lineparts[2].strip(),lineparts[3].strip(),lineparts[4].strip(),lineparts[5].strip(),lineparts[6].strip(),lineparts[7].strip())
processing.fix_seed(p)
batch_count = p.n_iter
#Clean up options
tmpl_pos = str(tmpl_pos).strip()
tmpl_neg = str(tmpl_neg).strip()
#Save extra parameters for the UI
p.extra_generation_params = {
"Create GIF": vid_gif,
"Create MP4": vid_mp4,
"Create WEBM": vid_webm,
"Total Time (s)": totaltime,
"FPS": fps,
"Initial Denoising Strength": denoising_strength,
"Initial Zoom Factor": zoom_factor,
"Initial X Pixel Shift": x_shift,
"Initial Y Pixel Shift": y_shift,
"Add Noise": add_noise,
"Noise Percentage": noise_strength,
"Denoise Decay": noise_decay,
"Denoise Decay Rate": decay_rate,
"Prompt Template Positive": tmpl_pos,
"Prompt Template Negative": tmpl_neg,
"Keyframe Data": prompts,
}
#save settings, just dump out the extra_generation dict
settings_filename = os.path.join(outpath, f"{str(outfilename)}_settings.txt")
with open(settings_filename, "w+", encoding="utf-8") as f:
json.dump(dict(p.extra_generation_params), f, ensure_ascii=False, indent=4)
#Check prompts. If no prompt given, but templates exist, set them.
if len(p.prompt.strip(",").strip()) == 0: p.prompt = tmpl_pos
if len(p.negative_prompt.strip(",").strip()) == 0: p.negative_prompt = tmpl_neg
if p.init_images[0] is None:
a = np.random.rand(p.width, p.height, 3)*255
p.init_images.append(Image.fromarray(a.astype('uint8')).convert('RGB'))
p.batch_size = 1
p.n_iter = 1
p.denoising_strength = denoising_strength
#For half life, or 0.5x every second, formula:
# decay_mult = 1/(2^(1/FPS))
decay_mult = 1 / (2 ** (float(decay_rate) / int(fps)))
#Zoom FPS scaler = zoom ^ (1/FPS)
zoom_factor = float(zoom_factor) ** (1/float(fps))
output_images, info = None, None
initial_seed = None
initial_info = None
grids = []
all_images = []
make_gif(outpath, outfilename, int(fps), False, True)
make_mp4(outpath, outfilename, int(fps), False, True)
make_webm(outpath, outfilename, int(fps), False, True)
loops = int(fps) * float(totaltime)
state.job_count = int(loops) * batch_count
initial_color_corrections = [processing.setup_color_correction(p.init_images[0])]
x_xhift_cumulitive = 0
y_shift_cumulitive = 0
x_shift_perframe = float(x_shift) / float(fps)
y_shift_perframe = float(y_shift) / float(fps)
for i in range(int(loops)):
if state.interrupted:
#Interrupt button pressed in WebUI
break
#Process Keyframes
if i in myprompts:
# Desnoise | Zoom | X Shift | Y shift | Positive Prompts | Negative Prompts | Seed
print(f"\r\nKeyframe at {i}: {myprompts[i]}\r\n")
p.denoising_strength = float(myprompts[i][0])
zoom_factor = float(myprompts[i][1]) ** (1/float(fps))
x_shift = float(myprompts[i][2])
y_shift = float(myprompts[i][3])
x_shift_perframe = x_shift / int(fps)
y_shift_perframe = y_shift / int(fps)
#If not prompt, continue previous prompts
if len(myprompts[i][4]) > 0: p.prompt = tmpl_pos + ", " + myprompts[i][4]
if len(myprompts[i][5]) > 0: p.negative_prompt = tmpl_neg + ", " + myprompts[i][5]
#If seed is blank, keep it the same as it was. Otherwise, set it. -1 will result in random seed.
if len(myprompts[i][6]) != 0:
p.seed = int(myprompts[i][6])
processing.fix_seed(p)
elif noise_decay:
p.denoising_strength = p.denoising_strength * decay_mult
p.n_iter = 1
p.batch_size = 1
p.do_not_save_grid = True
p.color_corrections = initial_color_corrections
state.job = f"Iteration {i + 1}/{int(loops)}"
processed = processing.process_images(p)
if initial_seed is None:
initial_seed = processed.seed
initial_info = processed.info
#Accumulate the pixel shift per frame, incase its < 1
x_shift_cumulitive = x_xhift_cumulitive + x_shift_perframe
y_shift_cumulitive = y_shift_cumulitive + y_shift_perframe
#Manipulate image to be passed to next iteration
init_img = processed.images[0]
p.init_images = [zoom_at2(init_img, int(x_shift_cumulitive), int(y_shift_cumulitive), zoom_factor)]
#p.init_images = [opencvtransform(init_img, 0, int(x_shift_cumulitive), int(y_shift_cumulitive), zoom_factor, False)]
if add_noise:
#print("Adding Noise!!")
p.init_images[0] = addnoise(p.init_images[0], noise_strength)
#Subtract the integer portion we just shifted.
x_shift_cumulitive = x_xhift_cumulitive - int(x_xhift_cumulitive)
y_shift_cumulitive = y_shift_cumulitive - int(y_shift_cumulitive)
p.seed = processed.seed + 1
#Save every seconds worth of frames to the output set displayed in UI
if (i % int(fps) == 0):
all_images.append(init_img)
#Save current image to folder manually, with specific name we can iterate over.
init_img.save(os.path.join(outpath, f"{outfilename}_{i:05}.png"))
#If not interrupted, make requested movies. Otherise the bat files exist.
make_gif(outpath, outfilename, int(fps), vid_gif, False)# & (not state.interrupted), False)
make_mp4(outpath, outfilename, int(fps), vid_mp4, False)# & (not state.interrupted), False)
make_webm(outpath, outfilename, int(fps), vid_webm, False)# & (not state.interrupted), False)
#display(all_images, initial_seed, initial_info)
#print("Video Rendered.\r\n")
processed = Processed(p, all_images, initial_seed, initial_info)
return processed