remove browser to extension
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124e44cf1e
commit
cef1b89aa2
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@ -1,3 +1,4 @@
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callbacks_model_loaded = []
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callbacks_ui_tabs = []
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callbacks_ui_settings = []
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@ -15,6 +16,7 @@ def model_loaded_callback(sd_model):
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def ui_tabs_callback():
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res = []
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for callback in callbacks_ui_tabs:
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res += callback() or []
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@ -82,7 +82,6 @@ parser.add_argument("--api", action='store_true', help="use api=True to launch t
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parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the api instead of the webui")
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parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI")
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parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None)
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parser.add_argument("--browse-all-images", action='store_true', help="Allow browsing all images by Image Browser", default=False)
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cmd_opts = parser.parse_args()
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restricted_opts = [
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@ -1104,7 +1104,7 @@ def create_ui(wrap_gradio_gpu_call):
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upscaling_crop = gr.Checkbox(label='Crop to fit', value=True)
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with gr.Group():
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extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers] , value=shared.sd_upscalers[0].name, type="index")
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extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
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with gr.Group():
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extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
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@ -1,57 +0,0 @@
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import csv, os, shutil
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import modules.scripts as scripts
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from modules import processing, shared, sd_samplers, images
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from modules.processing import Processed
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from modules.shared import opts
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import gradio
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class Script(scripts.Script):
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def title(self):
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return "Create inspiration images"
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def show(self, is_img2img):
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return True
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def ui(self, is_img2img):
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file = gradio.Files(label="Artist or styles name list. '.txt' files with one name per line",)
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with gradio.Row():
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prefix = gradio.Textbox("a painting in", label="Prompt words before artist or style name", file_count="multiple")
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suffix= gradio.Textbox("style", label="Prompt words after artist or style name")
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negative_prompt = gradio.Textbox("picture frame, portrait photo", label="Negative Prompt")
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with gradio.Row():
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batch_size = gradio.Number(1, label="Batch size")
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batch_count = gradio.Number(2, label="Batch count")
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return [batch_size, batch_count, prefix, suffix, negative_prompt, file]
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def run(self, p, batch_size, batch_count, prefix, suffix, negative_prompt, files):
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p.batch_size = int(batch_size)
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p.n_iterint = int(batch_count)
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p.negative_prompt = negative_prompt
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p.do_not_save_samples = True
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p.do_not_save_grid = True
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for file in files:
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tp = file.orig_name.split(".")[0]
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print(tp)
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path = os.path.join(opts.inspiration_dir, tp)
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if not os.path.exists(path):
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os.makedirs(path)
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f = open(file.name, "r")
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line = f.readline()
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while len(line) > 0:
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name = line.rstrip("\n").split(",")[0]
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line = f.readline()
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artist_path = os.path.join(path, name)
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if not os.path.exists(artist_path):
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os.mkdir(artist_path)
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if len(os.listdir(artist_path)) >= opts.inspiration_max_samples:
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continue
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p.prompt = f"{prefix} {name} {suffix}"
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print(p.prompt)
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processed = processing.process_images(p)
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for img in processed.images:
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i = 0
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filename = os.path.join(artist_path, format(0, "03d") + ".jpg")
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while os.path.exists(filename):
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i += 1
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filename = os.path.join(artist_path, format(i, "03d") + ".jpg")
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img.save(filename, quality=80)
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return processed
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