mirror of
https://github.com/artegoser/image-pluser-webui.git
synced 2024-11-05 20:23:58 +03:00
commit
1b259c886f
13 changed files with 273 additions and 88 deletions
2
.gitignore
vendored
2
.gitignore
vendored
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@ -150,3 +150,5 @@ cython_debug/
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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output
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112
app.py
112
app.py
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@ -1,98 +1,34 @@
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import datetime
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import gradio as gr
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from PIL import Image, ImageChops
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from processing.stacking import stacking
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import sys
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import importlib
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import pathlib
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import os
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from tqdm import tqdm
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import copy
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from tabs import tabs
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tabs_dir = pathlib.Path(__file__).parent / "tabs"
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def impluser(dir, method):
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files = os.listdir(dir)
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files = list(map(lambda x: os.path.join(dir, x), files))
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files = list(filter(lambda x: x.endswith(".png"), files))
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if method == "denoise":
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img = denoise(files)
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elif method == "startracks":
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img = startracks(files)
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elif method == "noise extractor":
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img = noise_extractor(files)
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elif method == "untrack":
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img = untrack(files)
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name = generate_name()
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img.save(name)
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return [name]
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def generate_name():
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# if not exists output create it
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if not os.path.exists("./output"):
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os.mkdir("./output")
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return f"./output/{datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}.png"
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def denoise(files):
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bias = 1
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image = Image.open(files[0])
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for file in tqdm(files):
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alpha = 1/bias
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im2 = Image.open(file)
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im3 = Image.blend(image, im2, alpha)
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image = im3
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bias += 1
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return image
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def startracks(files):
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image = Image.open(files[0])
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for file in tqdm(files):
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im2 = Image.open(file)
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im3 = ImageChops.lighter(image, im2)
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image = im3
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return image
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def noise_extractor(files):
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image = Image.open(files[0])
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for file in tqdm(files, unit=' images'):
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im2 = Image.open(file)
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im3 = ImageChops.difference(image, im2)
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image = im3
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return image
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def untrack(files):
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image = Image.open(files[0])
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for file in tqdm(files, unit=' images'):
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im2 = Image.open(file)
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im3 = ImageChops.darker(image, im2)
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image = im3
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return image
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all_tabs = []
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tab = None
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for tab_name in tabs:
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old_path = copy.deepcopy(sys.path)
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sys.path = [os.path.join(tabs_dir, tab_name)] + sys.path
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try:
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if tab is None:
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tab = importlib.import_module(f"app")
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else:
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tab = importlib.reload(tab)
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all_tabs.append((tab_name, tab.app))
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except Exception as e:
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print(f"Error loading tab ({tab_name}): {e}")
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with gr.Blocks() as app:
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with gr.Row():
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with gr.Column():
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directory = gr.Textbox(
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placeholder="A directory on the same machine where the server is running.", lines=1, label="Directory")
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methods = gr.Dropdown(
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choices=["denoise", "startracks", "noise extractor", "untrack"], value="denoise", label="Method")
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submit = gr.Button("Submit")
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for tab_name, tab in all_tabs:
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with gr.Tab(tab_name):
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tab.render()
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with gr.Column():
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output = gr.Gallery()
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submit.click(impluser, inputs=[directory, methods], outputs=[output])
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app.launch()
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14
methods/bulk_methods.py
Normal file
14
methods/bulk_methods.py
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@ -0,0 +1,14 @@
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from PIL import Image, ImageFilter
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def canny_edge(file_name):
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image = Image.open(file_name)
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image = image.convert("L")
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return image.filter(ImageFilter.FIND_EDGES)
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def sharpen(file_name):
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image = Image.open(file_name)
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return image.filter(ImageFilter.SHARPEN)
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49
methods/stack_methods.py
Normal file
49
methods/stack_methods.py
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@ -0,0 +1,49 @@
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from PIL import Image, ImageChops
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from tqdm import tqdm
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def denoise(files):
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bias = 1
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image = Image.open(files[0])
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for file in tqdm(files):
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alpha = 1/bias
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im2 = Image.open(file)
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im3 = Image.blend(image, im2, alpha)
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image = im3
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bias += 1
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return image
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def startracks(files):
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image = Image.open(files[0])
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for file in tqdm(files):
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im2 = Image.open(file)
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im3 = ImageChops.lighter(image, im2)
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image = im3
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return image
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def noise_extractor(files):
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image = Image.open(files[0])
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for file in tqdm(files, unit=' images'):
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im2 = Image.open(file)
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im3 = ImageChops.difference(image, im2)
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image = im3
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return image
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def untrack(files):
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image = Image.open(files[0])
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for file in tqdm(files, unit=' images'):
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im2 = Image.open(file)
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im3 = ImageChops.darker(image, im2)
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image = im3
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return image
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45
processing/bulk.py
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45
processing/bulk.py
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@ -0,0 +1,45 @@
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import ffmpeg
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import os
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from processing.utils import generate_name, get_date_text, generate_name_with_file_name
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from methods.bulk_methods import canny_edge, sharpen
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def images_to_video(directory, fps, img_ext, img_name_format, video_name, video_ext, video_dir):
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images_pattern = os.path.join(directory, f"{img_name_format}.{img_ext}")
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if video_dir:
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video_path = os.path.join(video_dir, f"{video_name}.{video_ext}")
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else:
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video_path = generate_name(
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extension=video_ext, name=video_name, subfolder="videos")
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ffmpeg.input(images_pattern,
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framerate=fps).output(video_path, pix_fmt='yuv420p').global_args("-y").run()
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def video_to_images(video_path, img_ext):
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images_pattern = generate_name(
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extension=img_ext, name=f"%d", subfolder=os.path.join("images", get_date_text()))
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ffmpeg.input(video_path).output(images_pattern).run()
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def bulk_processing(directory, out_directory, method):
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date = get_date_text()
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if method == "canny edge":
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run_bulk(canny_edge, directory, out_directory, date)
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elif method == "sharpen":
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run_bulk(sharpen, directory, out_directory, date)
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def run_bulk(func, directory, out_directory, date):
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for file in os.listdir(directory):
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img = func(os.path.join(directory, file))
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if out_directory:
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img_out_path = os.path.join(out_directory, file)
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else:
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img_out_path = generate_name_with_file_name(
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name=file, subfolder=os.path.join("images", date))
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img.save(img_out_path)
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24
processing/stacking.py
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24
processing/stacking.py
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from methods.stack_methods import denoise, startracks, noise_extractor, untrack
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import os
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from processing.utils import generate_name
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def stacking(dir, method):
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files = os.listdir(dir)
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files = list(map(lambda x: os.path.join(dir, x), files))
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files = list(filter(lambda x: x.endswith(".png"), files))
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if method == "denoise":
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img = denoise(files)
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elif method == "startracks":
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img = startracks(files)
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elif method == "noise extractor":
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img = noise_extractor(files)
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elif method == "untrack":
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img = untrack(files)
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name = generate_name()
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img.save(name)
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return [name]
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23
processing/utils.py
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23
processing/utils.py
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import os
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import datetime
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def generate_name(name=False, subfolder="stacked", extension="png", format='%Y-%m-%d_%H-%M-%S'):
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os.makedirs(os.path.join(".", "output", subfolder), exist_ok=True)
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if name is False or name == "":
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name = get_date_text(format)
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return os.path.join(".", "output", subfolder, f"{name}.{extension}")
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def generate_name_with_file_name(name, subfolder):
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os.makedirs(os.path.join(".", "output", subfolder), exist_ok=True)
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return os.path.join(".", "output", subfolder, name)
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def get_date_text(format='%Y-%m-%d_%H-%M-%S'):
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return datetime.datetime.now().strftime(format)
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@ -1,3 +1,4 @@
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ffmpeg_python==0.2.0
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gradio==3.27.0
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Pillow==9.5.0
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tqdm==4.65.0
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21
tabs/Bulk processing/app.py
Normal file
21
tabs/Bulk processing/app.py
Normal file
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import gradio as gr
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from processing.bulk import bulk_processing
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with gr.Blocks() as app:
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gr.Markdown(
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"Mass processing of images one at a time and saving to video if needed. # **WIP, not working**")
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with gr.Row():
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with gr.Column():
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directory = gr.Text(
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placeholder="A directory with many images.", lines=1, label="Directory")
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method = gr.Dropdown(
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choices=["canny edge", "sharpen"], value="canny edge", label="Method")
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with gr.Accordion("Advanced settings", open=False) as acc:
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out_dir = gr.Text(
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label="Output directory", placeholder="The directory where the processed photos will be saved. If not specified `./output/images`")
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submit = gr.Button("Submit")
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submit.click(
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fn=bulk_processing,
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inputs=[directory, out_dir, method],
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)
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30
tabs/Images to video/app.py
Normal file
30
tabs/Images to video/app.py
Normal file
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import gradio as gr
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from processing.bulk import images_to_video
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with gr.Blocks() as app:
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gr.Markdown("Convert images to video.")
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directory = gr.Text(
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placeholder="A directory with many images of the same size", label="Directory")
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fps = gr.Number(label="FPS", value=30, min=0)
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with gr.Accordion("Advanced settings", open=False) as acc:
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video_name = gr.Text(
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label="Video name", placeholder="Video name e.g. video. If not specified will be generated by time")
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video_ext = gr.Dropdown(label="Video extension", choices=[
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"mp4"], value="mp4")
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video_dir = gr.Text(
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label="Video directory", placeholder="The directory where the video will be saved. If not specified `./output/videos`")
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img_ext = gr.Dropdown(label="Image extension", choices=[
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"png", "jpg"], value="png")
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img_name_format = gr.Text(
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label="Image name format", placeholder="ffmpeg pattern e.g. %04d is (0000.png)", value="%d")
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submit = gr.Button("Submit")
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submit.click(
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fn=images_to_video,
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inputs=[directory, fps, img_ext, img_name_format,
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video_name, video_ext, video_dir],
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)
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18
tabs/Stacking/app.py
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18
tabs/Stacking/app.py
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import gradio as gr
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from processing.stacking import stacking
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with gr.Blocks() as app:
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gr.Markdown("Stacking images.")
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with gr.Row():
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with gr.Column():
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directory = gr.Text(
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placeholder="A directory with many images of the same size", lines=1, label="Directory")
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methods = gr.Dropdown(
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choices=["denoise", "startracks", "noise extractor", "untrack"], value="denoise", label="Method")
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submit = gr.Button("Submit")
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with gr.Column():
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output = gr.Gallery()
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submit.click(stacking, inputs=[
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directory, methods], outputs=[output])
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16
tabs/Video to images/app.py
Normal file
16
tabs/Video to images/app.py
Normal file
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import gradio as gr
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from processing.bulk import video_to_images
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with gr.Blocks() as app:
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gr.Markdown(
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"Convert video to images.")
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with gr.Row():
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with gr.Column():
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video = gr.Video(label="Video")
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with gr.Column():
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format = gr.Radio(
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choices=["png", "jpg"], value="png", label="Format of image")
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submit = gr.Button("Submit")
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submit.click(fn=video_to_images, inputs=[video, format])
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6
tabs/__init__.py
Normal file
6
tabs/__init__.py
Normal file
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tabs = [
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"Stacking",
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"Bulk processing",
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"Images to video",
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"Video to images"
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]
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