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Add missing comma for nsfw toggle in img2img #1028

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merged 1 commit into from
Sep 11, 2022
Merged

Add missing comma for nsfw toggle in img2img #1028

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36 changes: 18 additions & 18 deletions scripts/webui.py
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Original file line number Diff line number Diff line change
Expand Up @@ -812,7 +812,7 @@ def classToArrays( items, seed, n_iter ):
return all_seeds, n_iter, prompt_matrix_parts, all_prompts, needrows

def perform_masked_image_restoration(image, init_img, init_mask, mask_blur_strength, mask_restore, use_RealESRGAN, RealESRGAN):
if not mask_restore:
if not mask_restore:
return image
else:
init_mask = init_mask.filter(ImageFilter.GaussianBlur(mask_blur_strength))
Expand Down Expand Up @@ -840,7 +840,7 @@ def perform_color_correction(img_rgb, correction_target_lab, do_color_correction
except:
print("Install scikit-image to perform color correction")
return img_rgb

if not do_color_correction: return img_rgb
if correction_target_lab is None: return img_rgb

Expand All @@ -854,7 +854,7 @@ def perform_color_correction(img_rgb, correction_target_lab, do_color_correction
channel_axis=2
), cv2.COLOR_LAB2RGB).astype("uint8")
)
)
)

def process_images(
outpath, func_init, func_sample, prompt, seed, sampler_name, skip_grid, skip_save, batch_size,
Expand Down Expand Up @@ -1027,7 +1027,7 @@ def check_safety(x_image):
while(torch.cuda.memory_allocated()/1e6 >= mem):
time.sleep(1)

cur_variant_amount = variant_amount
cur_variant_amount = variant_amount
if variant_amount == 0.0:
# we manually generate all input noises because each one should have a specific seed
x = create_random_tensors(shape, seeds=seeds)
Expand Down Expand Up @@ -1114,10 +1114,10 @@ def check_safety(x_image):
gfpgan_image = Image.fromarray(gfpgan_sample)
gfpgan_image = perform_color_correction(gfpgan_image, correction_target, do_color_correction)
gfpgan_image = perform_masked_image_restoration(
gfpgan_image, init_img, init_mask,
gfpgan_image, init_img, init_mask,
mask_blur_strength, mask_restore,
use_RealESRGAN = False, RealESRGAN = None
)
)
gfpgan_metadata = copy.copy(metadata)
gfpgan_metadata.GFPGAN = True
ImageMetadata.set_on_image( gfpgan_image, gfpgan_metadata )
Expand All @@ -1137,7 +1137,7 @@ def check_safety(x_image):
esrgan_image = Image.fromarray(esrgan_sample)
esrgan_image = perform_color_correction(esrgan_image, correction_target, do_color_correction)
esrgan_image = perform_masked_image_restoration(
esrgan_image, init_img, init_mask,
esrgan_image, init_img, init_mask,
mask_blur_strength, mask_restore,
use_RealESRGAN, RealESRGAN
)
Expand All @@ -1159,7 +1159,7 @@ def check_safety(x_image):
gfpgan_esrgan_image = Image.fromarray(gfpgan_esrgan_sample)
gfpgan_esrgan_image = perform_color_correction(gfpgan_esrgan_image, correction_target, do_color_correction)
gfpgan_esrgan_image = perform_masked_image_restoration(
gfpgan_esrgan_image, init_img, init_mask,
gfpgan_esrgan_image, init_img, init_mask,
mask_blur_strength, mask_restore,
use_RealESRGAN, RealESRGAN
)
Expand All @@ -1175,7 +1175,7 @@ def check_safety(x_image):
output_images.append(image)

image = perform_masked_image_restoration(
image, init_img, init_mask,
image, init_img, init_mask,
mask_blur_strength, mask_restore,
# RealESRGAN image already processed in if-case above.
use_RealESRGAN = False, RealESRGAN = None
Expand Down Expand Up @@ -1505,7 +1505,7 @@ def init():
#let's try and find where init_image is 0's
#shape is probably (3,width,height)?

if image_editor_mode == "Uncrop":
if image_editor_mode == "Uncrop":
_image=image.numpy()[0]
_mask=np.ones((_image.shape[1],_image.shape[2]))

Expand All @@ -1526,7 +1526,7 @@ def init():
boundingbox=np.zeros(shape=(height,width))
boundingbox[colstart+PAD_IMG:colend-PAD_IMG,rowstart+PAD_IMG:rowend-PAD_IMG]=1
boundingbox=blurArr(boundingbox,4)

#this is the mask for outpainting
PAD_MASK=24
boundingbox2=np.zeros(shape=(height,width))
Expand Down Expand Up @@ -1557,7 +1557,7 @@ def init():
init_image = init_image.to(device)
init_image = repeat(init_image, '1 ... -> b ...', b=batch_size)
init_latent = (model if not opt.optimized else modelFS).get_first_stage_encoding((model if not opt.optimized else modelFS).encode_first_stage(init_image)) # move to latent space

if opt.optimized:
mem = torch.cuda.memory_allocated()/1e6
modelFS.to("cpu")
Expand Down Expand Up @@ -1617,7 +1617,7 @@ def sample(init_data, x, conditioning, unconditional_conditioning, sampler_name)

# turn on color correction for loopback to prevent known issue of color drift
do_color_correction = True

for i in range(n_iter):
if do_color_correction and i == 0:
correction_target = cv2.cvtColor(np.asarray(init_img.copy()), cv2.COLOR_RGB2LAB)
Expand Down Expand Up @@ -1658,9 +1658,9 @@ def sample(init_data, x, conditioning, unconditional_conditioning, sampler_name)
write_info_files=write_info_files,
write_sample_info_to_log_file=write_sample_info_to_log_file,
jpg_sample=jpg_sample,
job_info=job_info,
job_info=job_info,
do_color_correction=do_color_correction,
correction_target=correction_target
correction_target=correction_target
)

if initial_seed is None:
Expand Down Expand Up @@ -2074,7 +2074,7 @@ def processLDSR(image):
if 1 in imgproc_toggles:
if imgproc_upscale_toggles == 0:
ModelLoader(['GFPGAN','LDSR'],False,True) # Unload unused models
ModelLoader(['RealESGAN'],True,False,imgproc_realesrgan_model_name) # Load used models
ModelLoader(['RealESGAN'],True,False,imgproc_realesrgan_model_name) # Load used models
elif imgproc_upscale_toggles == 1:
ModelLoader(['GFPGAN','LDSR'],False,True) # Unload unused models
ModelLoader(['RealESGAN','model'],True,False) # Load used models
Expand Down Expand Up @@ -2306,7 +2306,7 @@ def run_RealESRGAN(image, model_name: str):
'Write sample info files',
'Write sample info to one file',
'jpg samples',
'Color correction (always enabled on loopback mode)'
'Color correction (always enabled on loopback mode)',
'Filter NSFW content',
]
# removed for now becuase of Image Lab implementation
Expand Down Expand Up @@ -2412,7 +2412,7 @@ def run(self):
'inbrowser': opt.inbrowser,
'server_name': '0.0.0.0',
'server_port': opt.port,
'share': opt.share,
'share': opt.share,
'show_error': True
}
if not opt.share:
Expand Down