mirror of
https://github.com/sd-webui/stable-diffusion-webui.git
synced 2024-12-14 23:02:00 +03:00
Merge branch 'sd-webui:dev' into dev
This commit is contained in:
ZeroCool
GitHub
commit
cf924ca11f
@ -7,6 +7,7 @@
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SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
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cd $SCRIPT_DIR
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export PYTHONPATH=$SCRIPT_DIR
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MODEL_DIR="${SCRIPT_DIR}/model_cache"
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# Array of model files to pre-download
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@ -31,6 +32,7 @@ ENV_UPDATED=0
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ENV_MODIFIED=$(date -r $ENV_FILE "+%s")
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ENV_MODIFED_FILE="${SCRIPT_DIR}/.env_updated"
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if [[ -f $ENV_MODIFED_FILE ]]; then ENV_MODIFIED_CACHED=$(<${ENV_MODIFED_FILE}); else ENV_MODIFIED_CACHED=0; fi
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export PIP_EXISTS_ACTION=w
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# Create/update conda env if needed
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if ! conda env list | grep ".*${ENV_NAME}.*" >/dev/null 2>&1; then
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@ -812,7 +812,7 @@ def oxlamon_matrix(prompt, seed, n_iter, batch_size):
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return all_seeds, n_iter, prompt_matrix_parts, all_prompts, needrows
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def perform_masked_image_restoration(image, init_img, init_mask, mask_blur_strength, mask_restore, use_RealESRGAN, RealESRGAN):
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if not mask_restore:
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if not mask_restore:
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return image
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else:
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init_mask = init_mask.filter(ImageFilter.GaussianBlur(mask_blur_strength))
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@ -840,7 +840,7 @@ def perform_color_correction(img_rgb, correction_target_lab, do_color_correction
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except:
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print("Install scikit-image to perform color correction")
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return img_rgb
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if not do_color_correction: return img_rgb
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if correction_target_lab is None: return img_rgb
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@ -854,7 +854,7 @@ def perform_color_correction(img_rgb, correction_target_lab, do_color_correction
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channel_axis=2
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), cv2.COLOR_LAB2RGB).astype("uint8")
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)
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)
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)
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def process_images(
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outpath, func_init, func_sample, prompt, seed, sampler_name, skip_grid, skip_save, batch_size,
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@ -1027,7 +1027,7 @@ def process_images(
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while(torch.cuda.memory_allocated()/1e6 >= mem):
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time.sleep(1)
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cur_variant_amount = variant_amount
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cur_variant_amount = variant_amount
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if variant_amount == 0.0:
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# we manually generate all input noises because each one should have a specific seed
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x = create_random_tensors(shape, seeds=seeds)
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@ -1114,10 +1114,10 @@ def process_images(
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gfpgan_image = Image.fromarray(gfpgan_sample)
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gfpgan_image = perform_color_correction(gfpgan_image, correction_target, do_color_correction)
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gfpgan_image = perform_masked_image_restoration(
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gfpgan_image, init_img, init_mask,
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gfpgan_image, init_img, init_mask,
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mask_blur_strength, mask_restore,
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use_RealESRGAN = False, RealESRGAN = None
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)
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)
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gfpgan_metadata = copy.copy(metadata)
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gfpgan_metadata.GFPGAN = True
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ImageMetadata.set_on_image( gfpgan_image, gfpgan_metadata )
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@ -1137,7 +1137,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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esrgan_image = Image.fromarray(esrgan_sample)
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esrgan_image = perform_color_correction(esrgan_image, correction_target, do_color_correction)
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esrgan_image = perform_masked_image_restoration(
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esrgan_image, init_img, init_mask,
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esrgan_image, init_img, init_mask,
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mask_blur_strength, mask_restore,
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use_RealESRGAN, RealESRGAN
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)
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@ -1159,7 +1159,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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gfpgan_esrgan_image = Image.fromarray(gfpgan_esrgan_sample)
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gfpgan_esrgan_image = perform_color_correction(gfpgan_esrgan_image, correction_target, do_color_correction)
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gfpgan_esrgan_image = perform_masked_image_restoration(
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gfpgan_esrgan_image, init_img, init_mask,
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gfpgan_esrgan_image, init_img, init_mask,
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mask_blur_strength, mask_restore,
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use_RealESRGAN, RealESRGAN
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)
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@ -1175,7 +1175,7 @@ skip_save, skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size,
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output_images.append(image)
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image = perform_masked_image_restoration(
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image, init_img, init_mask,
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image, init_img, init_mask,
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mask_blur_strength, mask_restore,
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# RealESRGAN image already processed in if-case above.
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use_RealESRGAN = False, RealESRGAN = None
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@ -1505,7 +1505,7 @@ def img2img(prompt: str, image_editor_mode: str, mask_mode: str, mask_blur_stren
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#let's try and find where init_image is 0's
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#shape is probably (3,width,height)?
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if image_editor_mode == "Uncrop":
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if image_editor_mode == "Uncrop":
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_image=image.numpy()[0]
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_mask=np.ones((_image.shape[1],_image.shape[2]))
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@ -1526,7 +1526,7 @@ def img2img(prompt: str, image_editor_mode: str, mask_mode: str, mask_blur_stren
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boundingbox=np.zeros(shape=(height,width))
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boundingbox[colstart+PAD_IMG:colend-PAD_IMG,rowstart+PAD_IMG:rowend-PAD_IMG]=1
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boundingbox=blurArr(boundingbox,4)
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#this is the mask for outpainting
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PAD_MASK=24
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boundingbox2=np.zeros(shape=(height,width))
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@ -1557,7 +1557,7 @@ def img2img(prompt: str, image_editor_mode: str, mask_mode: str, mask_blur_stren
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init_image = init_image.to(device)
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init_image = repeat(init_image, '1 ... -> b ...', b=batch_size)
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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
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if opt.optimized:
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mem = torch.cuda.memory_allocated()/1e6
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modelFS.to("cpu")
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@ -1617,7 +1617,7 @@ def img2img(prompt: str, image_editor_mode: str, mask_mode: str, mask_blur_stren
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# turn on color correction for loopback to prevent known issue of color drift
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do_color_correction = True
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for i in range(n_iter):
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if do_color_correction and i == 0:
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correction_target = cv2.cvtColor(np.asarray(init_img.copy()), cv2.COLOR_RGB2LAB)
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@ -1658,9 +1658,9 @@ def img2img(prompt: str, image_editor_mode: str, mask_mode: str, mask_blur_stren
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write_info_files=write_info_files,
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write_sample_info_to_log_file=write_sample_info_to_log_file,
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jpg_sample=jpg_sample,
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job_info=job_info,
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job_info=job_info,
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do_color_correction=do_color_correction,
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correction_target=correction_target
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correction_target=correction_target
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)
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if initial_seed is None:
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@ -2074,7 +2074,7 @@ def imgproc(image,image_batch,imgproc_prompt,imgproc_toggles, imgproc_upscale_to
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if 1 in imgproc_toggles:
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if imgproc_upscale_toggles == 0:
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ModelLoader(['GFPGAN','LDSR'],False,True) # Unload unused models
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ModelLoader(['RealESGAN'],True,False,imgproc_realesrgan_model_name) # Load used models
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ModelLoader(['RealESGAN'],True,False,imgproc_realesrgan_model_name) # Load used models
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elif imgproc_upscale_toggles == 1:
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ModelLoader(['GFPGAN','LDSR'],False,True) # Unload unused models
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ModelLoader(['RealESGAN','model'],True,False) # Load used models
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@ -2306,7 +2306,7 @@ img2img_toggles = [
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'Write sample info files',
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'Write sample info to one file',
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'jpg samples',
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'Color correction (always enabled on loopback mode)'
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'Color correction (always enabled on loopback mode)',
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'Filter NSFW content',
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]
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# removed for now becuase of Image Lab implementation
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@ -2412,7 +2412,7 @@ class ServerLauncher(threading.Thread):
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'inbrowser': opt.inbrowser,
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'server_name': '0.0.0.0',
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'server_port': opt.port,
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'share': opt.share,
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'share': opt.share,
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'show_error': True
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}
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if not opt.share:
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