Merge pull request #1 from artegoser/new-features

New features

.gitignore

@@ -150,3 +150,5 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+
+output

app.py

@@ -1,98 +1,34 @@
-import datetime
 import gradio as gr
-from PIL import Image, ImageChops
+from processing.stacking import stacking
+import sys
+import importlib
+import pathlib
 import os
-from tqdm import tqdm
+import copy
+from tabs import tabs
+
+tabs_dir = pathlib.Path(__file__).parent / "tabs"
 
 
-def impluser(dir, method):
+all_tabs = []
-
+tab = None
-    files = os.listdir(dir)
+for tab_name in tabs:
-    files = list(map(lambda x: os.path.join(dir, x), files))
+    old_path = copy.deepcopy(sys.path)
-    files = list(filter(lambda x: x.endswith(".png"), files))
+    sys.path = [os.path.join(tabs_dir, tab_name)] + sys.path
-
+    try:
-    if method == "denoise":
+        if tab is None:
-        img = denoise(files)
+            tab = importlib.import_module(f"app")
-    elif method == "startracks":
+        else:
-        img = startracks(files)
+            tab = importlib.reload(tab)
-    elif method == "noise extractor":
+        all_tabs.append((tab_name, tab.app))
-        img = noise_extractor(files)
-    elif method == "untrack":
-        img = untrack(files)
-
-    name = generate_name()
-    img.save(name)
-
-    return [name]
-
-
-def generate_name():
-    # if not exists output create it
-    if not os.path.exists("./output"):
-        os.mkdir("./output")
-
-    return f"./output/{datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}.png"
-
-
-def denoise(files):
-    bias = 1
-    image = Image.open(files[0])
-    for file in tqdm(files):
-
-        alpha = 1/bias
-
-        im2 = Image.open(file)
-        im3 = Image.blend(image, im2, alpha)
-
-        image = im3
-
-        bias += 1
-
-    return image
-
-
-def startracks(files):
-    image = Image.open(files[0])
-    for file in tqdm(files):
-        im2 = Image.open(file)
-        im3 = ImageChops.lighter(image, im2)
-        image = im3
-
-    return image
-
-
-def noise_extractor(files):
-    image = Image.open(files[0])
-    for file in tqdm(files, unit=' images'):
-        im2 = Image.open(file)
-        im3 = ImageChops.difference(image, im2)
-        image = im3
-
-    return image
-
-
-def untrack(files):
-    image = Image.open(files[0])
-    for file in tqdm(files, unit=' images'):
-        im2 = Image.open(file)
-        im3 = ImageChops.darker(image, im2)
-        image = im3
-
-    return image
 
+    except Exception as e:
+        print(f"Error loading tab ({tab_name}): {e}")
 
 with gr.Blocks() as app:
-    with gr.Row():
+    for tab_name, tab in all_tabs:
-        with gr.Column():
+        with gr.Tab(tab_name):
-            directory = gr.Textbox(
+            tab.render()
-                placeholder="A directory on the same machine where the server is running.", lines=1, label="Directory")
-            methods = gr.Dropdown(
-                choices=["denoise", "startracks", "noise extractor", "untrack"], value="denoise", label="Method")
-            submit = gr.Button("Submit")
 
-        with gr.Column():
-            output = gr.Gallery()
-
-        submit.click(impluser, inputs=[directory, methods], outputs=[output])
 
 app.launch()

methods/bulk_methods.py

@@ -0,0 +1,14 @@
+from PIL import Image, ImageFilter
+
+
+def canny_edge(file_name):
+    image = Image.open(file_name)
+
+    image = image.convert("L")
+
+    return image.filter(ImageFilter.FIND_EDGES)
+
+
+def sharpen(file_name):
+    image = Image.open(file_name)
+    return image.filter(ImageFilter.SHARPEN)

methods/stack_methods.py

@@ -0,0 +1,49 @@
+from PIL import Image, ImageChops
+from tqdm import tqdm
+
+
+def denoise(files):
+    bias = 1
+    image = Image.open(files[0])
+    for file in tqdm(files):
+
+        alpha = 1/bias
+
+        im2 = Image.open(file)
+        im3 = Image.blend(image, im2, alpha)
+
+        image = im3
+
+        bias += 1
+
+    return image
+
+
+def startracks(files):
+    image = Image.open(files[0])
+    for file in tqdm(files):
+        im2 = Image.open(file)
+        im3 = ImageChops.lighter(image, im2)
+        image = im3
+
+    return image
+
+
+def noise_extractor(files):
+    image = Image.open(files[0])
+    for file in tqdm(files, unit=' images'):
+        im2 = Image.open(file)
+        im3 = ImageChops.difference(image, im2)
+        image = im3
+
+    return image
+
+
+def untrack(files):
+    image = Image.open(files[0])
+    for file in tqdm(files, unit=' images'):
+        im2 = Image.open(file)
+        im3 = ImageChops.darker(image, im2)
+        image = im3
+
+    return image

processing/bulk.py

@@ -0,0 +1,45 @@
+
+import ffmpeg
+import os
+from processing.utils import generate_name, get_date_text, generate_name_with_file_name
+from methods.bulk_methods import canny_edge, sharpen
+
+
+def images_to_video(directory, fps, img_ext, img_name_format, video_name, video_ext, video_dir):
+    images_pattern = os.path.join(directory, f"{img_name_format}.{img_ext}")
+
+    if video_dir:
+        video_path = os.path.join(video_dir, f"{video_name}.{video_ext}")
+    else:
+        video_path = generate_name(
+            extension=video_ext, name=video_name, subfolder="videos")
+
+    ffmpeg.input(images_pattern,
+                 framerate=fps).output(video_path, pix_fmt='yuv420p').global_args("-y").run()
+
+
+def video_to_images(video_path, img_ext):
+
+    images_pattern = generate_name(
+        extension=img_ext, name=f"%d", subfolder=os.path.join("images", get_date_text()))
+
+    ffmpeg.input(video_path).output(images_pattern).run()
+
+
+def bulk_processing(directory, out_directory, method):
+    date = get_date_text()
+    if method == "canny edge":
+        run_bulk(canny_edge, directory, out_directory, date)
+    elif method == "sharpen":
+        run_bulk(sharpen, directory, out_directory, date)
+
+
+def run_bulk(func, directory, out_directory, date):
+    for file in os.listdir(directory):
+        img = func(os.path.join(directory, file))
+        if out_directory:
+            img_out_path = os.path.join(out_directory, file)
+        else:
+            img_out_path = generate_name_with_file_name(
+                name=file, subfolder=os.path.join("images", date))
+        img.save(img_out_path)

processing/stacking.py

@@ -0,0 +1,24 @@
+from methods.stack_methods import denoise, startracks, noise_extractor, untrack
+import os
+from processing.utils import generate_name
+
+
+def stacking(dir, method):
+
+    files = os.listdir(dir)
+    files = list(map(lambda x: os.path.join(dir, x), files))
+    files = list(filter(lambda x: x.endswith(".png"), files))
+
+    if method == "denoise":
+        img = denoise(files)
+    elif method == "startracks":
+        img = startracks(files)
+    elif method == "noise extractor":
+        img = noise_extractor(files)
+    elif method == "untrack":
+        img = untrack(files)
+
+    name = generate_name()
+    img.save(name)
+
+    return [name]

processing/utils.py

@@ -0,0 +1,23 @@
+import os
+import datetime
+
+
+def generate_name(name=False, subfolder="stacked", extension="png", format='%Y-%m-%d_%H-%M-%S'):
+
+    os.makedirs(os.path.join(".", "output", subfolder), exist_ok=True)
+
+    if name is False or name == "":
+        name = get_date_text(format)
+
+    return os.path.join(".", "output", subfolder, f"{name}.{extension}")
+
+
+def generate_name_with_file_name(name, subfolder):
+
+    os.makedirs(os.path.join(".", "output", subfolder), exist_ok=True)
+
+    return os.path.join(".", "output", subfolder, name)
+
+
+def get_date_text(format='%Y-%m-%d_%H-%M-%S'):
+    return datetime.datetime.now().strftime(format)

requirements.txt

@@ -1,3 +1,4 @@
+ffmpeg_python==0.2.0
 gradio==3.27.0
 Pillow==9.5.0
 tqdm==4.65.0

tabs/Bulk processing/app.py

@@ -0,0 +1,21 @@
+import gradio as gr
+from processing.bulk import bulk_processing
+
+with gr.Blocks() as app:
+    gr.Markdown(
+        "Mass processing of images one at a time and saving to video if needed.   # **WIP, not working**")
+    with gr.Row():
+        with gr.Column():
+            directory = gr.Text(
+                placeholder="A directory with many images.", lines=1, label="Directory")
+            method = gr.Dropdown(
+                choices=["canny edge", "sharpen"], value="canny edge", label="Method")
+
+            with gr.Accordion("Advanced settings", open=False) as acc:
+                out_dir = gr.Text(
+                    label="Output directory", placeholder="The directory where the processed photos will be saved. If not specified `./output/images`")
+            submit = gr.Button("Submit")
+            submit.click(
+                fn=bulk_processing,
+                inputs=[directory, out_dir, method],
+            )

tabs/Images to video/app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from processing.bulk import images_to_video
+
+with gr.Blocks() as app:
+    gr.Markdown("Convert images to video.")
+    directory = gr.Text(
+        placeholder="A directory with many images of the same size", label="Directory")
+
+    fps = gr.Number(label="FPS", value=30, min=0)
+
+    with gr.Accordion("Advanced settings", open=False) as acc:
+        video_name = gr.Text(
+            label="Video name", placeholder="Video name e.g. video. If not specified will be generated by time")
+        video_ext = gr.Dropdown(label="Video extension", choices=[
+            "mp4"], value="mp4")
+        video_dir = gr.Text(
+            label="Video directory", placeholder="The directory where the video will be saved. If not specified `./output/videos`")
+
+        img_ext = gr.Dropdown(label="Image extension", choices=[
+            "png", "jpg"], value="png")
+        img_name_format = gr.Text(
+            label="Image name format", placeholder="ffmpeg pattern e.g. %04d is (0000.png)", value="%d")
+
+    submit = gr.Button("Submit")
+
+    submit.click(
+        fn=images_to_video,
+        inputs=[directory, fps, img_ext, img_name_format,
+                video_name, video_ext, video_dir],
+    )

tabs/Stacking/app.py

@@ -0,0 +1,18 @@
+import gradio as gr
+from processing.stacking import stacking
+
+with gr.Blocks() as app:
+    gr.Markdown("Stacking images.")
+    with gr.Row():
+        with gr.Column():
+            directory = gr.Text(
+                placeholder="A directory with many images of the same size", lines=1, label="Directory")
+            methods = gr.Dropdown(
+                choices=["denoise", "startracks", "noise extractor", "untrack"], value="denoise", label="Method")
+            submit = gr.Button("Submit")
+
+        with gr.Column():
+            output = gr.Gallery()
+
+        submit.click(stacking, inputs=[
+            directory, methods], outputs=[output])

tabs/Video to images/app.py

@@ -0,0 +1,16 @@
+import gradio as gr
+from processing.bulk import video_to_images
+
+with gr.Blocks() as app:
+    gr.Markdown(
+        "Convert video to images.")
+    with gr.Row():
+        with gr.Column():
+
+            video = gr.Video(label="Video")
+
+        with gr.Column():
+            format = gr.Radio(
+                choices=["png", "jpg"], value="png", label="Format of image")
+            submit = gr.Button("Submit")
+            submit.click(fn=video_to_images, inputs=[video, format])

tabs/__init__.py

@@ -0,0 +1,6 @@
+tabs = [
+    "Stacking",
+    "Bulk processing",
+    "Images to video",
+    "Video to images"
+]