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Slight turbo mode cleanup. Added questionable code to protect people who may modify the settings code (or that may hurt them - It could go either way)

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pull/14/head
Adam Letts 3 years ago
parent 0e366efcf9
commit 1704be96f8
2 changed files with 54 additions and 52 deletions
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  1. 53
      Disco_Diffusion.ipynb
  2. 53
      disco.py

53
Disco_Diffusion.ipynb
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@ -1119,30 +1119,31 @@
"\n",
" ### Turbo mode - skip some diffusions, use 3d morph for clarity and to save time\n",
" turbo_blend = False # default for non-turbo frame saving\n",
" if turbo_mode == True and frame_num == turbo_preroll: #start tracking oldframe\n",
" next_step_pil.save('oldFrameScaled.png')#stash for later blending \n",
" if turbo_mode == True and frame_num > turbo_preroll:\n",
" #set up 2 warped image sequences, old & new, to blend toward new diff image\n",
" old_frame = do_3d_step('oldFrameScaled.png', frame_num, midas_model, midas_transform)\n",
" old_frame.save('oldFrameScaled.png')\n",
" if frame_num % int(turbo_steps) != 0: \n",
" print('turbo skip this frame: skipping clip diffusion steps')\n",
" filename = f'{args.batch_name}({args.batchNum})_{frame_num:04}.png'\n",
" blend_factor = ((frame_num % int(turbo_steps))+1)/int(turbo_steps)\n",
" print('turbo skip this frame: skipping clip diffusion steps and saving blended frame')\n",
" newWarpedImg = cv2.imread('prevFrameScaled.png')#this is already updated..\n",
" oldWarpedImg = cv2.imread('oldFrameScaled.png')\n",
" blendedImage = cv2.addWeighted(newWarpedImg, blend_factor, oldWarpedImg,1-blend_factor, 0.0)\n",
" cv2.imwrite(f'{batchFolder}/{filename}',blendedImage)\n",
" next_step_pil.save(f'{img_filepath}') # save it also as prev_frame to feed next iteration\n",
" turbo_blend = False\n",
" continue\n",
" else:\n",
" #if not a skip frame, will run diffusion and need to blend.\n",
" oldWarpedImg = cv2.imread('prevFrameScaled.png')\n",
" cv2.imwrite(f'oldFrameScaled.png',oldWarpedImg)#swap in for blending later \n",
" turbo_blend = True # flag to blend frames after diff generated...\n",
" print('clip/diff this frame - generate clip diff image')\n",
" if turbo_mode:\n",
" if frame_num == turbo_preroll: #start tracking oldframe\n",
" next_step_pil.save('oldFrameScaled.png')#stash for later blending \n",
" elif frame_num > turbo_preroll:\n",
" #set up 2 warped image sequences, old & new, to blend toward new diff image\n",
" old_frame = do_3d_step('oldFrameScaled.png', frame_num, midas_model, midas_transform)\n",
" old_frame.save('oldFrameScaled.png')\n",
" if frame_num % int(turbo_steps) != 0: \n",
" print('turbo skip this frame: skipping clip diffusion steps')\n",
" filename = f'{args.batch_name}({args.batchNum})_{frame_num:04}.png'\n",
" blend_factor = ((frame_num % int(turbo_steps))+1)/int(turbo_steps)\n",
" print('turbo skip this frame: skipping clip diffusion steps and saving blended frame')\n",
" newWarpedImg = cv2.imread('prevFrameScaled.png')#this is already updated..\n",
" oldWarpedImg = cv2.imread('oldFrameScaled.png')\n",
" blendedImage = cv2.addWeighted(newWarpedImg, blend_factor, oldWarpedImg,1-blend_factor, 0.0)\n",
" cv2.imwrite(f'{batchFolder}/{filename}',blendedImage)\n",
" next_step_pil.save(f'{img_filepath}') # save it also as prev_frame to feed next iteration\n",
" turbo_blend = False\n",
" continue\n",
" else:\n",
" #if not a skip frame, will run diffusion and need to blend.\n",
" oldWarpedImg = cv2.imread('prevFrameScaled.png')\n",
" cv2.imwrite(f'oldFrameScaled.png',oldWarpedImg)#swap in for blending later \n",
" turbo_blend = True # flag to blend frames after diff generated...\n",
" print('clip/diff this frame - generate clip diff image')\n",
"\n",
" init_image = 'prevFrameScaled.png'\n",
" init_scale = args.frames_scale\n",
@ -3006,11 +3007,11 @@
" batchNum = int(run_to_resume)\n",
" if resume_from_frame == 'latest':\n",
" start_frame = len(glob(batchFolder+f\"/{batch_name}({batchNum})_*.png\"))\n",
" if turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:\n",
" if animation_mode != '3D' and turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:\n",
" start_frame = start_frame - (start_frame % int(turbo_steps))\n",
" else:\n",
" start_frame = int(resume_from_frame)+1\n",
" if turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:\n",
" if animation_mode != '3D' and turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:\n",
" start_frame = start_frame - (start_frame % int(turbo_steps))\n",
" if retain_overwritten_frames is True:\n",
" existing_frames = len(glob(batchFolder+f\"/{batch_name}({batchNum})_*.png\"))\n",

53
disco.py
Unescape View File

@ -1026,30 +1026,31 @@ def do_run():
### Turbo mode - skip some diffusions, use 3d morph for clarity and to save time
turbo_blend = False # default for non-turbo frame saving
if turbo_mode == True and frame_num == turbo_preroll: #start tracking oldframe
next_step_pil.save('oldFrameScaled.png')#stash for later blending
if turbo_mode == True and frame_num > turbo_preroll:
#set up 2 warped image sequences, old & new, to blend toward new diff image
old_frame = do_3d_step('oldFrameScaled.png', frame_num, midas_model, midas_transform)
old_frame.save('oldFrameScaled.png')
if frame_num % int(turbo_steps) != 0:
print('turbo skip this frame: skipping clip diffusion steps')
filename = f'{args.batch_name}({args.batchNum})_{frame_num:04}.png'
blend_factor = ((frame_num % int(turbo_steps))+1)/int(turbo_steps)
print('turbo skip this frame: skipping clip diffusion steps and saving blended frame')
newWarpedImg = cv2.imread('prevFrameScaled.png')#this is already updated..
oldWarpedImg = cv2.imread('oldFrameScaled.png')
blendedImage = cv2.addWeighted(newWarpedImg, blend_factor, oldWarpedImg,1-blend_factor, 0.0)
cv2.imwrite(f'{batchFolder}/{filename}',blendedImage)
next_step_pil.save(f'{img_filepath}') # save it also as prev_frame to feed next iteration
turbo_blend = False
continue
else:
#if not a skip frame, will run diffusion and need to blend.
oldWarpedImg = cv2.imread('prevFrameScaled.png')
cv2.imwrite(f'oldFrameScaled.png',oldWarpedImg)#swap in for blending later
turbo_blend = True # flag to blend frames after diff generated...
print('clip/diff this frame - generate clip diff image')
if turbo_mode:
if frame_num == turbo_preroll: #start tracking oldframe
next_step_pil.save('oldFrameScaled.png')#stash for later blending
elif frame_num > turbo_preroll:
#set up 2 warped image sequences, old & new, to blend toward new diff image
old_frame = do_3d_step('oldFrameScaled.png', frame_num, midas_model, midas_transform)
old_frame.save('oldFrameScaled.png')
if frame_num % int(turbo_steps) != 0:
print('turbo skip this frame: skipping clip diffusion steps')
filename = f'{args.batch_name}({args.batchNum})_{frame_num:04}.png'
blend_factor = ((frame_num % int(turbo_steps))+1)/int(turbo_steps)
print('turbo skip this frame: skipping clip diffusion steps and saving blended frame')
newWarpedImg = cv2.imread('prevFrameScaled.png')#this is already updated..
oldWarpedImg = cv2.imread('oldFrameScaled.png')
blendedImage = cv2.addWeighted(newWarpedImg, blend_factor, oldWarpedImg,1-blend_factor, 0.0)
cv2.imwrite(f'{batchFolder}/{filename}',blendedImage)
next_step_pil.save(f'{img_filepath}') # save it also as prev_frame to feed next iteration
turbo_blend = False
continue
else:
#if not a skip frame, will run diffusion and need to blend.
oldWarpedImg = cv2.imread('prevFrameScaled.png')
cv2.imwrite(f'oldFrameScaled.png',oldWarpedImg)#swap in for blending later
turbo_blend = True # flag to blend frames after diff generated...
print('clip/diff this frame - generate clip diff image')
init_image = 'prevFrameScaled.png'
init_scale = args.frames_scale
@ -2829,11 +2830,11 @@ if resume_run:
batchNum = int(run_to_resume)
if resume_from_frame == 'latest':
start_frame = len(glob(batchFolder+f"/{batch_name}({batchNum})_*.png"))
if turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:
if animation_mode != '3D' and turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:
start_frame = start_frame - (start_frame % int(turbo_steps))
else:
start_frame = int(resume_from_frame)+1
if turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:
if animation_mode != '3D' and turbo_mode == True and start_frame > turbo_preroll and start_frame % int(turbo_steps) != 0:
start_frame = start_frame - (start_frame % int(turbo_steps))
if retain_overwritten_frames is True:
existing_frames = len(glob(batchFolder+f"/{batch_name}({batchNum})_*.png"))

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