Surn commited on
Commit
a6bc325
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1 Parent(s): e56c022

Gradio 5.22.0

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LUT/neons.cube ADDED
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+ # Generated 3D LUT from 8x8 PNG
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+ TITLE "Converted 8x8x8 LUT"
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+ LUT_3D_SIZE 8
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README.md CHANGED
@@ -5,7 +5,7 @@ colorFrom: yellow
5
  colorTo: purple
6
  sdk: gradio
7
  python_version: 3.10.13
8
- sdk_version: 5.21.0
9
  app_file: app.py
10
  pinned: false
11
  short_description: Transform Your Images into Mesmerizing Hexagon Grids
 
5
  colorTo: purple
6
  sdk: gradio
7
  python_version: 3.10.13
8
+ sdk_version: 5.22.0
9
  app_file: app.py
10
  pinned: false
11
  short_description: Transform Your Images into Mesmerizing Hexagon Grids
app.py CHANGED
@@ -772,7 +772,7 @@ with gr.Blocks(css_paths="style_20250314.css", title=title, theme='Surn/beeuty',
772
  apply_lut_button = gr.Button("Apply Filter (LUT)", elem_classes="solid", elem_id="apply_lut_button")
773
 
774
  lut_file.change(get_filename, inputs=[lut_file], outputs=[lut_filename])
775
- lut_filename.change(show_lut, inputs=[lut_filename, lut_example_image], outputs=[lut_example_image])
776
  apply_lut_button.click(
777
  lambda lut_filename, input_image: gr.Warning("Please upload an Input Image to get started.") if input_image is None else apply_lut_to_image_path(lut_filename, input_image)[0],
778
  inputs=[lut_filename, input_image],
 
772
  apply_lut_button = gr.Button("Apply Filter (LUT)", elem_classes="solid", elem_id="apply_lut_button")
773
 
774
  lut_file.change(get_filename, inputs=[lut_file], outputs=[lut_filename])
775
+ lut_filename.change(show_lut, inputs=[lut_filename, input_image], outputs=[lut_example_image])
776
  apply_lut_button.click(
777
  lambda lut_filename, input_image: gr.Warning("Please upload an Input Image to get started.") if input_image is None else apply_lut_to_image_path(lut_filename, input_image)[0],
778
  inputs=[lut_filename, input_image],
modules/file_utils.py ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # modules/file_utils
2
+ import os
3
+ import modules.constants as constants
4
+ #import shutil
5
+ from pathlib import Path
6
+
7
+ def cleanup_temp_files():
8
+ for file_path in constants.temp_files:
9
+ try:
10
+ os.remove(file_path)
11
+ except Exception as e:
12
+ print(f"Failed to delete temp file {file_path}: {e}")
13
+ print("Temp files cleaned up. Goodbye")
14
+
15
+ def get_file_parts(file_path: str):
16
+ # Split the path into directory and filename
17
+ directory, filename = os.path.split(file_path)
18
+
19
+ # Split the filename into name and extension
20
+ name, ext = os.path.splitext(filename)
21
+
22
+ # Convert the extension to lowercase
23
+ new_ext = ext.lower()
24
+ return directory, filename, name, ext, new_ext
25
+
26
+ def rename_file_to_lowercase_extension(file_path: str) -> str:
27
+ """
28
+ Renames a file's extension to lowercase in place.
29
+
30
+ Parameters:
31
+ file_path (str): The original file path.
32
+
33
+ Returns:
34
+ str: The new file path with the lowercase extension.
35
+
36
+ Raises:
37
+ OSError: If there is an error renaming the file (e.g., file not found, permissions issue).
38
+ """
39
+ directory, filename, name, ext, new_ext = get_file_parts(file_path)
40
+ # If the extension changes, rename the file
41
+ if ext != new_ext:
42
+ new_filename = name + new_ext
43
+ new_file_path = os.path.join(directory, new_filename)
44
+ try:
45
+ os.rename(file_path, new_file_path)
46
+ print(f"Rename {file_path} to {new_file_path}\n")
47
+ except Exception as e:
48
+ print(f"os.rename failed: {e}. Falling back to binary copy operation.")
49
+ try:
50
+ # Read the file in binary mode and write it to new_file_path
51
+ with open(file_path, 'rb') as f:
52
+ data = f.read()
53
+ with open(new_file_path, 'wb') as f:
54
+ f.write(data)
55
+ print(f"Copied {file_path} to {new_file_path}\n")
56
+ # Optionally, remove the original file after copying
57
+ #os.remove(file_path)
58
+ except Exception as inner_e:
59
+ print(f"Failed to copy file from {file_path} to {new_file_path}: {inner_e}")
60
+ raise inner_e
61
+ return new_file_path
62
+ else:
63
+ return file_path
modules/image_utils.py CHANGED
@@ -1,4 +1,4 @@
1
- # modules/image_utils.py
2
  import os
3
  from io import BytesIO
4
  import cairosvg
@@ -15,12 +15,54 @@ from modules.color_utils import (
15
  detect_color_format,
16
  update_color_opacity
17
  )
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
18
  def get_image_from_dict(image_path):
19
  if isinstance(image_path, dict) :
20
  if 'composite' in image_path:
21
  image_path = image_path.get('composite')
22
  elif 'image' in image_path:
23
  image_path = image_path.get('image')
 
 
24
  else:
25
  print("\n Unknown image dictionary.\n")
26
  raise UserWarning("Unknown image dictionary.")
@@ -42,11 +84,16 @@ def open_image(image_path):
42
  Raises:
43
  Exception: If there is an error opening the image.
44
  """
 
45
  if isinstance(image_path, Image.Image):
46
  return image_path
 
 
 
 
 
47
  import requests
48
  try:
49
- image_path, is_dict = get_image_from_dict(image_path)
50
  # Strip leading and trailing double quotation marks, if present
51
  image_path = image_path.strip('"')
52
  if image_path.startswith('http'):
@@ -97,33 +144,34 @@ def build_prerendered_images(images_list):
97
  # print(filtered_maps)
98
  def build_prerendered_images_by_quality(quality_limit, key='file'):
99
  """
100
- Retrieve and sort file paths from PRE_RENDERED_MAPS_JSON_LEVELS where quality is less than or equal to the given limit.
101
- The sorting order matches pre_rendered_maps_paths based on quality and a case-insensitive alphanumeric key.
102
-
103
  Args:
104
- quality_limit (int): The quality threshold.
105
- key (str): The key to extract the file path from each map info (default is 'file').
106
-
107
  Returns:
108
- list: A list of sorted file paths meeting the quality criteria.
109
- """
110
- # Sort the PRE_RENDERED_MAPS_JSON_LEVELS items by quality and alphanumeric key
111
- sorted_maps = sorted(
112
- PRE_RENDERED_MAPS_JSON_LEVELS.items(),
113
- key=lambda x: (
114
- x[1]['quality'],
115
- ''.join(char.lower() for char in x[0] if char.isalnum())
116
- )
117
- )
118
-
119
- # Filter and extract the file paths that meet the quality limit
120
- images_list = [
121
- map_info[key].replace("\\", "/")
122
- for _, map_info in sorted_maps
123
- if map_info['quality'] <= quality_limit
124
  ]
125
 
126
- return build_prerendered_images(images_list)
 
 
 
 
 
127
 
128
 
129
  def build_encoded_images(images_list):
@@ -271,7 +319,7 @@ def resize_image_with_aspect_ratio(image, target_width, target_height):
271
  original_width, original_height = image.size
272
  target_aspect = target_width / target_height
273
  original_aspect = original_width / original_height
274
-
275
  # Decide whether to fit width or height
276
  if original_aspect > target_aspect:
277
  # Image is wider than target aspect ratio
@@ -284,6 +332,7 @@ def resize_image_with_aspect_ratio(image, target_width, target_height):
284
 
285
  # Resize the image
286
  resized_image = image.resize((new_width, new_height), Image.LANCZOS)
 
287
 
288
  # Create a new image with target dimensions and black background
289
  new_image = Image.new("RGB", (target_width, target_height), (0, 0, 0))
@@ -368,8 +417,11 @@ def multiply_and_blend_images(base_image, image2, alpha_percent=50):
368
  Returns:
369
  PIL.Image.Image: The blended image.
370
  """
 
 
371
  alpha = alpha_percent / 100.0
372
  if isinstance(base_image, str):
 
373
  base_image = open_image(base_image)
374
  if isinstance(image2, str):
375
  image2 = open_image(image2)
@@ -383,7 +435,10 @@ def multiply_and_blend_images(base_image, image2, alpha_percent=50):
383
 
384
  # Blend the multiplied result with the original
385
  blended_image = Image.blend(base_image, multiplied_image, alpha)
386
-
 
 
 
387
  return blended_image
388
 
389
  def alpha_composite_with_control(base_image, image_with_alpha, alpha_percent=100):
@@ -398,9 +453,12 @@ def alpha_composite_with_control(base_image, image_with_alpha, alpha_percent=100
398
  Returns:
399
  PIL.Image.Image: The resulting image after alpha compositing.
400
  """
 
 
401
  image_with_alpha, isdict = get_image_from_dict(image_with_alpha)
402
  alpha_multiplier = alpha_percent / 100.0
403
  if isinstance(base_image, str):
 
404
  base_image = open_image(base_image)
405
  if isinstance(image_with_alpha, str):
406
  image_with_alpha = open_image(image_with_alpha)
@@ -418,7 +476,11 @@ def alpha_composite_with_control(base_image, image_with_alpha, alpha_percent=100
418
 
419
  # Composite the images
420
  result = Image.alpha_composite(base_image, image_with_alpha)
421
-
 
 
 
 
422
  return result
423
 
424
  def apply_alpha_mask(image, mask_image, invert = False):
@@ -497,8 +559,33 @@ def is_3dlut_row(row: List[str]) -> bool:
497
  except ValueError:
498
  return False
499
 
 
500
 
501
- def read_lut(path_lut: Union[str, os.PathLike], num_channels: int = 3) -> ImageFilter.Color3DLUT:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
502
  """
503
  Read LUT from a raw file.
504
 
@@ -522,7 +609,31 @@ def read_lut(path_lut: Union[str, os.PathLike], num_channels: int = 3) -> ImageF
522
  lut_table = [row2val(row) for row in lut_raw if is_3dlut_row(row.split(" "))]
523
  return ImageFilter.Color3DLUT(size, lut_table, num_channels)
524
 
525
- def apply_lut(img: Image, lut_path: str = "", lut: ImageFilter.Color3DLUT = None) -> Image:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
526
  """
527
  Apply a LUT to an image and return a PIL Image with the LUT applied.
528
 
@@ -542,11 +653,33 @@ def apply_lut(img: Image, lut_path: str = "", lut: ImageFilter.Color3DLUT = None
542
  if lut is None:
543
  if lut_path == "":
544
  raise ValueError("Either lut_path or lut argument must be provided.")
545
- lut = read_lut(lut_path)
546
  return img.filter(lut)
547
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
548
  def show_lut(lut_filename: str, lut_example_image: Image = default_lut_example_img) -> Image:
549
- if lut_filename is not None:
 
 
 
550
  try:
551
  lut_example_image = apply_lut(lut_example_image, lut_filename)
552
  except Exception as e:
@@ -555,33 +688,29 @@ def show_lut(lut_filename: str, lut_example_image: Image = default_lut_example_i
555
  lut_example_image = open_image(default_lut_example_img)
556
  return lut_example_image
557
 
558
-
559
-
560
- def convert_rgb_to_rgba_safe(image: Image) -> Image:
561
- """
562
- Converts an RGB image to RGBA by adding an alpha channel.
563
- Ensures that the original image remains unaltered.
564
-
565
- Parameters:
566
- image (PIL.Image.Image): The RGB image to convert.
567
-
568
- Returns:
569
- PIL.Image.Image: The converted RGBA image.
570
- """
571
- if image.mode != 'RGB':
572
- if image.mode == 'RGBA':
573
- return image
574
- elif image.mode == 'P':
575
- # Convert palette image to RGBA
576
- image = image.convert('RGB')
577
- else:
578
- raise ValueError("Unsupported image mode for conversion to RGBA.")
579
- # Create a copy of the image to avoid modifying the original
580
- rgba_image = image.copy()
581
- # Optionally, set a default alpha value (e.g., fully opaque)
582
- alpha = Image.new('L', rgba_image.size, 255) # 255 for full opacity
583
- rgba_image.putalpha(alpha)
584
- return rgba_image
585
 
586
  def apply_lut_to_image_path(lut_filename: str, image_path: str) -> tuple[Image, str]:
587
  """
@@ -595,9 +724,24 @@ def apply_lut_to_image_path(lut_filename: str, image_path: str) -> tuple[Image,
595
  Returns:
596
  tuple: A tuple containing the PIL Image object with the LUT applied and the new image path as a string.
597
  """
 
 
 
598
  if image_path is None:
599
  raise UserWarning("No image provided.")
600
  return None, None
 
 
 
 
 
 
 
 
 
 
 
 
601
  path = Path(image_path)
602
  img = open_image(image_path)
603
  if not ((path.suffix.lower() == '.png' and img.mode == 'RGBA')):
@@ -609,18 +753,139 @@ def apply_lut_to_image_path(lut_filename: str, image_path: str) -> tuple[Image,
609
  img, new_image_path = convert_to_rgba_png(image_path)
610
  else:
611
  img, new_image_path = convert_to_rgba_png(image_path)
612
- delete_image(image_path)
 
613
  else:
614
- new_image_path = image_path
615
- if lut_filename is not None:
 
 
 
616
  try:
617
- img = apply_lut(img, lut_filename)
618
  except Exception as e:
619
  print(f"BAD LUT: Error applying LUT {str(e)}.")
 
 
 
 
 
620
  img.save(new_image_path, format='PNG')
621
- return img, str(new_image_path)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
622
 
623
  ############################################# RGBA ###########################################################
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
624
 
625
  # Example usage
626
  # convert_jpg_to_rgba('input.jpg', 'output.png')
@@ -646,12 +911,15 @@ def convert_jpg_to_rgba(input_path) -> tuple[Image, str]:
646
 
647
  # Check if the input file exists
648
  if not input_path.exists():
649
- raise FileNotFoundError(f"The file {input_path} does not exist.")
 
 
 
650
 
651
  # Check file extension first to skip unnecessary processing
652
  if input_path.suffix.lower() not in ('.jpg', '.jpeg'):
653
  print(f"Skipping conversion: {input_path} is not a JPG or JPEG file.")
654
- return Image.open(input_path), str(output_path)
655
 
656
  print(f"Converting to PNG: {input_path} is a JPG or JPEG file.")
657
 
@@ -699,7 +967,7 @@ def convert_to_rgba_png(file_path: str) -> tuple[Image, str]:
699
  img = open_image(file_path)
700
  print(f"Opened image: {file_path}\n")
701
  # Handle ICO files
702
- if file_path.lower().endswith('.ico'):
703
  rgba_img = img.convert('RGBA')
704
  new_file_path = Path(file_path).with_suffix('.png')
705
  rgba_img.save(new_file_path, format='PNG')
@@ -771,22 +1039,22 @@ def resize_all_images_in_folder(target_width: int, output_folder: str = "resized
771
  with Image.open(file_path) as img:
772
  # Convert to RGB if needed (handles RGBA, CMYK, etc.)
773
  if img.mode != 'RGB':
774
- img = img.convert('RGB')
775
  # Calculate target height maintaining aspect ratio
776
  original_width, original_height = img.size
777
  aspect_ratio = original_height / original_width
778
- target_height = int(target_width * aspect_ratio)
779
  # Resize using the reference function
780
- resized_img = resize_image_with_aspect_ratio(img, target_width, target_height)
781
  # Create output filename
782
- output_filename = output_path / f"{file_prefix}{file_path.name}"
783
  # Save the resized image
784
- resized_img.save(output_filename, quality=95)
785
  successful += 1
786
- print(f"Successfully resized: {file_path.name}")
787
  except Exception as e:
788
  failed += 1
789
- print(f"Failed to resize {file_path.name}: {str(e)}")
790
 
791
  print(f"\nResizing complete. Successfully processed: {successful}, Failed: {failed}")
792
  return successful, failed
@@ -832,3 +1100,40 @@ def print_json():
832
  for key, value in PRE_RENDERED_MAPS_JSON_LEVELS.items():
833
  print(f" '{key}': {{'file': '{value['file']}', 'thumbnail': '{value['thumbnail']}', 'quality': {value['quality']}}},")
834
  print("}")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # modules/image_utils.py
2
  import os
3
  from io import BytesIO
4
  import cairosvg
 
15
  detect_color_format,
16
  update_color_opacity
17
  )
18
+ from modules.file_utils import rename_file_to_lowercase_extension, get_file_parts
19
+
20
+
21
+
22
+
23
+ def save_image_to_temp_png(image_source, user_dir: str = None, file_name: str = None):
24
+ """
25
+ Opens an image from a file path, URL, or DataURL and saves it as a PNG in the user's temporary directory.
26
+
27
+ Parameters:
28
+ image_source (str, dict or PIL.Image.Image): The source of the image to open.
29
+
30
+ Returns:
31
+ str: The file path of the saved PNG image in the temporary directory.
32
+ """
33
+ import tempfile
34
+ import uuid
35
+
36
+ # Open the image using the existing utility function
37
+ img = open_image(image_source)
38
+
39
+ # Ensure the image is in a format that supports PNG (convert if necessary)
40
+ if img.mode not in ("RGB", "RGBA"):
41
+ img = img.convert("RGBA")
42
+
43
+ # Generate a unique filename in the system temporary directory
44
+ if user_dir is None:
45
+ user_dir = tempfile.gettempdir()
46
+
47
+ if file_name is None:
48
+ file_name = "{uuid.uuid4()}"
49
+
50
+ temp_filepath = os.path.join(user_dir, file_name.lower() + ".png")
51
+ os.makedirs(user_dir, exist_ok=True)
52
+
53
+ # Save the image as PNG
54
+ img.save(temp_filepath, format="PNG")
55
+
56
+ return temp_filepath
57
+
58
  def get_image_from_dict(image_path):
59
  if isinstance(image_path, dict) :
60
  if 'composite' in image_path:
61
  image_path = image_path.get('composite')
62
  elif 'image' in image_path:
63
  image_path = image_path.get('image')
64
+ elif 'background' in image_path:
65
+ image_path = image_path.get('background')
66
  else:
67
  print("\n Unknown image dictionary.\n")
68
  raise UserWarning("Unknown image dictionary.")
 
84
  Raises:
85
  Exception: If there is an error opening the image.
86
  """
87
+
88
  if isinstance(image_path, Image.Image):
89
  return image_path
90
+ elif isinstance(image_path, dict):
91
+ image_path, is_dict = get_image_from_dict(image_path)
92
+
93
+ image_path = rename_file_to_lowercase_extension(image_path)
94
+
95
  import requests
96
  try:
 
97
  # Strip leading and trailing double quotation marks, if present
98
  image_path = image_path.strip('"')
99
  if image_path.startswith('http'):
 
144
  # print(filtered_maps)
145
  def build_prerendered_images_by_quality(quality_limit, key='file'):
146
  """
147
+ Retrieve and sort file paths from PRE_RENDERED_MAPS_JSON_LEVELS where quality is <= quality_limit.
148
+ Sorts by quality and case-insensitive alphanumeric key.
149
+
150
  Args:
151
+ quality_limit (int): Maximum quality threshold
152
+ key (str): Key to extract file path from map info (default: 'file')
153
+
154
  Returns:
155
+ tuple: (sorted file paths list, list of corresponding map names)
156
+ """
157
+ # Pre-compute lowercase alphanumeric key once per item
158
+ def get_sort_key(item):
159
+ name, info = item
160
+ return (info['quality'], ''.join(c for c in name.lower() if c.isalnum()))
161
+
162
+ # Single pass: sort and filter
163
+ filtered_maps = [
164
+ (info[key].replace("\\", "/"), name)
165
+ for name, info in sorted(PRE_RENDERED_MAPS_JSON_LEVELS.items(), key=get_sort_key)
166
+ if info['quality'] <= quality_limit
 
 
 
 
167
  ]
168
 
169
+ # Split into separate lists efficiently
170
+ if filtered_maps:
171
+ #file_paths, map_names = zip(*filtered_maps)
172
+ #return (build_prerendered_images(file_paths), list(map_names))
173
+ return [(open_image(file_path), map_name) for file_path, map_name in filtered_maps]
174
+ return (None,"")
175
 
176
 
177
  def build_encoded_images(images_list):
 
319
  original_width, original_height = image.size
320
  target_aspect = target_width / target_height
321
  original_aspect = original_width / original_height
322
+ #print(f"Original size: {image.size}\ntarget_aspect: {target_aspect}\noriginal_aspect: {original_aspect}\n")
323
  # Decide whether to fit width or height
324
  if original_aspect > target_aspect:
325
  # Image is wider than target aspect ratio
 
332
 
333
  # Resize the image
334
  resized_image = image.resize((new_width, new_height), Image.LANCZOS)
335
+ #print(f"Resized size: {resized_image.size}\n")
336
 
337
  # Create a new image with target dimensions and black background
338
  new_image = Image.new("RGB", (target_width, target_height), (0, 0, 0))
 
417
  Returns:
418
  PIL.Image.Image: The blended image.
419
  """
420
+ name = None
421
+ directory = None
422
  alpha = alpha_percent / 100.0
423
  if isinstance(base_image, str):
424
+ directory, _, name,_,_ = get_file_parts(base_image)
425
  base_image = open_image(base_image)
426
  if isinstance(image2, str):
427
  image2 = open_image(image2)
 
435
 
436
  # Blend the multiplied result with the original
437
  blended_image = Image.blend(base_image, multiplied_image, alpha)
438
+ if name is not None:
439
+ new_image_path = os.path.join(directory, name + f"_mb{str(alpha_percent)}.png")
440
+ blended_image.save(new_image_path)
441
+ return new_image_path
442
  return blended_image
443
 
444
  def alpha_composite_with_control(base_image, image_with_alpha, alpha_percent=100):
 
453
  Returns:
454
  PIL.Image.Image: The resulting image after alpha compositing.
455
  """
456
+ name = None
457
+ directory = None
458
  image_with_alpha, isdict = get_image_from_dict(image_with_alpha)
459
  alpha_multiplier = alpha_percent / 100.0
460
  if isinstance(base_image, str):
461
+ directory, _, name,_, new_ext = get_file_parts(base_image)
462
  base_image = open_image(base_image)
463
  if isinstance(image_with_alpha, str):
464
  image_with_alpha = open_image(image_with_alpha)
 
476
 
477
  # Composite the images
478
  result = Image.alpha_composite(base_image, image_with_alpha)
479
+ if name is not None:
480
+ new_image_path = os.path.join(directory, name + f"_alpha{str(alpha_percent)}.png")
481
+ result.save(new_image_path)
482
+ return new_image_path
483
+ return blended_image
484
  return result
485
 
486
  def apply_alpha_mask(image, mask_image, invert = False):
 
559
  except ValueError:
560
  return False
561
 
562
+ def get_lut_type(path_lut: Union[str, os.PathLike], num_channels: int = 3) -> str:
563
 
564
+ with open(path_lut) as f:
565
+ lines = f.read().splitlines()
566
+
567
+ lut_type = "3D" # Initially assume 3D LUT
568
+ size = None
569
+ table = []
570
+
571
+ # Parse the file
572
+ for line in lines:
573
+ line = line.strip()
574
+ if line.startswith("#") or not line:
575
+ continue # Skip comments and empty lines
576
+ parts = line.split()
577
+ if parts[0] == "LUT_3D_SIZE":
578
+ size = int(parts[1])
579
+ lut_type = "3D"
580
+ elif parts[0] == "LUT_1D_SIZE":
581
+ size = int(parts[1])
582
+ lut_type = "1D"
583
+ elif is_3dlut_row(parts):
584
+ table.append(tuple(float(val) for val in parts))
585
+ return lut_type
586
+
587
+
588
+ def read_3d_lut(path_lut: Union[str, os.PathLike], num_channels: int = 3) -> ImageFilter.Color3DLUT:
589
  """
590
  Read LUT from a raw file.
591
 
 
609
  lut_table = [row2val(row) for row in lut_raw if is_3dlut_row(row.split(" "))]
610
  return ImageFilter.Color3DLUT(size, lut_table, num_channels)
611
 
612
+ def apply_1d_lut(image, lut_file):
613
+ # Read the 1D LUT
614
+ with open(lut_file) as f:
615
+ lines = f.read().splitlines()
616
+ table = []
617
+ for line in lines:
618
+ if not line.startswith(("#", "LUT", "TITLE", "DOMAIN")) and line.strip():
619
+ values = [float(v) for v in line.split()]
620
+ table.append(tuple(values))
621
+
622
+ # Convert image to grayscale
623
+ if image.mode != 'L':
624
+ image = image.convert('L')
625
+ img_array = np.array(image) / 255.0 # Normalize to [0, 1]
626
+
627
+ # Map grayscale values to colors
628
+ lut_size = len(table)
629
+ indices = (img_array * (lut_size - 1)).astype(int)
630
+ colors = np.array(table)[indices]
631
+
632
+ # Create RGB image
633
+ rgb_image = Image.fromarray((colors * 255).astype(np.uint8), mode='RGB')
634
+ return rgb_image
635
+
636
+ def apply_3d_lut(img: Image, lut_path: str = "", lut: ImageFilter.Color3DLUT = None) -> Image:
637
  """
638
  Apply a LUT to an image and return a PIL Image with the LUT applied.
639
 
 
653
  if lut is None:
654
  if lut_path == "":
655
  raise ValueError("Either lut_path or lut argument must be provided.")
656
+ lut = read_3d_lut(lut_path)
657
  return img.filter(lut)
658
 
659
+ def apply_lut(image, lut_filename: str) -> Image:
660
+ """
661
+ Apply a LUT to an image and return the result.
662
+ Args:
663
+ image (str or PIL.Image.Image): The image to apply the LUT to.
664
+ lut_filename (str): The path to the LUT file.
665
+ Returns:
666
+ PIL.Image.Image: The image with the LUT applied.
667
+ """
668
+ if isinstance(image, str):
669
+ image = open_image(image)
670
+ if lut_filename is not None:
671
+ if (get_lut_type(lut_filename) == "3D"):
672
+ lut = read_3d_lut(lut_filename)
673
+ image = apply_3d_lut(image, lut=lut)
674
+ else:
675
+ image = apply_1d_lut(image, lut_filename)
676
+ return image
677
+
678
  def show_lut(lut_filename: str, lut_example_image: Image = default_lut_example_img) -> Image:
679
+ if lut_example_image is None:
680
+ lut_example_image = default_lut_example_img
681
+
682
+ if lut_filename is not None:
683
  try:
684
  lut_example_image = apply_lut(lut_example_image, lut_filename)
685
  except Exception as e:
 
688
  lut_example_image = open_image(default_lut_example_img)
689
  return lut_example_image
690
 
691
+ def apply_1d_lut(image, lut_file):
692
+ # Read the 1D LUT
693
+ with open(lut_file) as f:
694
+ lines = f.read().splitlines()
695
+ table = []
696
+ for line in lines:
697
+ if not line.startswith(("#", "LUT", "TITLE", "DOMAIN")) and line.strip():
698
+ values = [float(v) for v in line.split()]
699
+ table.append(tuple(values))
700
+
701
+ # Convert image to grayscale
702
+ if image.mode != 'L':
703
+ image = image.convert('L')
704
+ img_array = np.array(image) / 255.0 # Normalize to [0, 1]
705
+
706
+ # Map grayscale values to colors
707
+ lut_size = len(table)
708
+ indices = (img_array * (lut_size - 1)).astype(int)
709
+ colors = np.array(table)[indices]
710
+
711
+ # Create RGB image
712
+ rgb_image = Image.fromarray((colors * 255).astype(np.uint8), mode='RGB')
713
+ return rgb_image
 
 
 
 
714
 
715
  def apply_lut_to_image_path(lut_filename: str, image_path: str) -> tuple[Image, str]:
716
  """
 
724
  Returns:
725
  tuple: A tuple containing the PIL Image object with the LUT applied and the new image path as a string.
726
  """
727
+ import gradio as gr
728
+
729
+ img_lut = None
730
  if image_path is None:
731
  raise UserWarning("No image provided.")
732
  return None, None
733
+
734
+ # Split the path into directory and filename
735
+ directory, file_name = os.path.split(image_path)
736
+ lut_directory, lut_file_name = os.path.split(lut_filename)
737
+
738
+ # Split the filename into name and extension
739
+ name, ext = os.path.splitext(file_name)
740
+ lut_name, lut_ext = os.path.splitext(lut_file_name)
741
+
742
+ # Convert the extension to lowercase
743
+ new_ext = ext.lower()
744
+
745
  path = Path(image_path)
746
  img = open_image(image_path)
747
  if not ((path.suffix.lower() == '.png' and img.mode == 'RGBA')):
 
753
  img, new_image_path = convert_to_rgba_png(image_path)
754
  else:
755
  img, new_image_path = convert_to_rgba_png(image_path)
756
+ if image_path != new_image_path:
757
+ delete_image(image_path)
758
  else:
759
+ # ensure the file extension is lower_case, otherwise leave as is
760
+ new_filename = name + new_ext
761
+ new_image_path = os.path.join(directory, new_filename)
762
+ # Apply the LUT to the image
763
+ if (lut_filename is not None and img is not None):
764
  try:
765
+ img_lut = apply_lut(img, lut_filename)
766
  except Exception as e:
767
  print(f"BAD LUT: Error applying LUT {str(e)}.")
768
+ if img_lut is not None:
769
+ new_filename = name + "_"+ lut_name + new_ext
770
+ new_image_path = os.path.join(directory, new_filename)
771
+ #delete_image(image_path) - renamed with lut name
772
+ img = img_lut
773
  img.save(new_image_path, format='PNG')
774
+ print(f"Image with LUT saved as {new_image_path}")
775
+ return img, gr.update(value=str(new_image_path))
776
+
777
+ from PIL import Image
778
+ import numpy as np
779
+
780
+ def png_to_cube(input_png_path, output_cube_path, lut_size=17):
781
+ # Example usage
782
+ # png_to_cube(input_file, output_file, lut_size=17)
783
+
784
+ # Open the PNG file
785
+ img = Image.open(input_png_path)
786
+ # Ensure the image is 512x512
787
+ if img.size != (512, 512):
788
+ raise ValueError("Input PNG must be 512x512 pixels.")
789
+ # Convert to RGB and normalize to 0-1 range
790
+ pixels = np.array(img.convert("RGB")) / 255.0
791
+ # Calculate the step size for sampling (512 / 17 ≈ 30 pixels per step)
792
+ step = 512 // lut_size
793
+ # Open the output .cube file
794
+ with open(output_cube_path, "w") as f:
795
+ # Write .cube header
796
+ f.write('# Generated by PNG to LUT converter\n')
797
+ f.write('TITLE "Converted LUT"\n')
798
+ f.write(f'LUT_3D_SIZE {lut_size}\n')
799
+ f.write('DOMAIN_MIN 0.0 0.0 0.0\n')
800
+ f.write('DOMAIN_MAX 1.0 1.0 1.0\n')
801
+ # Iterate over the 3D LUT grid (R, G, B)
802
+ for b in range(lut_size): # Blue channel
803
+ for g in range(lut_size): # Green channel
804
+ for r in range(lut_size): # Red channel
805
+ # Map LUT coordinates to PNG coordinates
806
+ # Assume the PNG is laid out with:
807
+ # - X-axis (horizontal) = Red
808
+ # - Y-axis (vertical) = Green + Blue slices
809
+ x = r * step + step // 2 # Center of each Red step
810
+ y = (g + b * lut_size) * step + step // 2 # Green + Blue offset
811
+ # Ensure coordinates stay within bounds
812
+ x = min(x, 511)
813
+ y = min(y, 511)
814
+ # Get RGB value from the PNG
815
+ rgb = pixels[y, x]
816
+ # Write RGB values to .cube file (normalized 0-1)
817
+ f.write(f"{rgb[0]:.6f} {rgb[1]:.6f} {rgb[2]:.6f}\n")
818
+ print(f"Conversion complete. LUT saved to {output_cube_path}")
819
+
820
+ def png_8x8_to_3d_cube(input_png_path, output_cube_path, lut_size=8):
821
+ # Example usage: png_8x8_to_3d_cube(input_file, output_file, lut_size=8)
822
+ # Open the PNG file
823
+ img = Image.open(input_png_path)
824
+ # Ensure the image is 512x512
825
+ if img.size != (512, 512):
826
+ raise ValueError("Input PNG must be 512x512 pixels.")
827
+ # Convert to RGB and normalize to 0-1 range
828
+ pixels = np.array(img.convert("RGB")) / 255.0
829
+ # Grid parameters
830
+ grid_size = 8 # 8x8 boxes
831
+ box_size = 512 // grid_size # 64 pixels per box
832
+ step = box_size // lut_size # 64 ÷ 8 = 8 pixels per step
833
+ # Open the output .cube file
834
+ with open(output_cube_path, "w") as f:
835
+ # Write .cube header for 3D LUT
836
+ f.write('# Generated 3D LUT from 8x8 PNG\n')
837
+ f.write('TITLE "Converted 8x8x8 LUT"\n')
838
+ f.write(f'LUT_3D_SIZE {lut_size}\n')
839
+ f.write('DOMAIN_MIN 0.0 0.0 0.0\n')
840
+ f.write('DOMAIN_MAX 1.0 1.0 1.0\n')
841
+ # Iterate over the 3D LUT (R, G, B)
842
+ for b in range(lut_size): # Blue axis (rows of the 8x8 grid)
843
+ for g in range(lut_size): # Green axis (columns of the 8x8 grid)
844
+ for r in range(lut_size): # Red axis (within each box)
845
+ # Map to the 8x8 grid
846
+ box_row = b # Blue selects the row
847
+ box_col = g # Green selects the column
848
+ # Starting coordinates of the current box
849
+ box_x = box_col * box_size
850
+ box_y = box_row * box_size
851
+ # Sample within the box (R varies horizontally, G vertically)
852
+ x = box_x + r * step + step // 2 # Center of Red step
853
+ y = box_y + g * step + step // 2 # Center of Green step (reuse g for consistency)
854
+ # Ensure coordinates stay within bounds
855
+ x = min(x, 511)
856
+ y = min(y, 511)
857
+ # Get RGB value from the PNG
858
+ rgb = pixels[y, x]
859
+ # Write RGB values to .cube file
860
+ f.write(f"{rgb[0]:.6f} {rgb[1]:.6f} {rgb[2]:.6f}\n")
861
+ print(f"3D LUT conversion complete. Saved to {output_cube_path}")
862
 
863
  ############################################# RGBA ###########################################################
864
+ def convert_rgb_to_rgba_safe(image: Image) -> Image:
865
+ """
866
+ Converts an RGB image to RGBA by adding an alpha channel.
867
+ Ensures that the original image remains unaltered.
868
+
869
+ Parameters:
870
+ image (PIL.Image.Image): The RGB image to convert.
871
+
872
+ Returns:
873
+ PIL.Image.Image: The converted RGBA image.
874
+ """
875
+ if image.mode != 'RGB':
876
+ if image.mode == 'RGBA':
877
+ return image
878
+ elif image.mode == 'P':
879
+ # Convert palette image to RGBA
880
+ image = image.convert('RGB')
881
+ else:
882
+ raise ValueError("Unsupported image mode for conversion to RGBA.")
883
+ # Create a copy of the image to avoid modifying the original
884
+ rgba_image = image.copy()
885
+ # Optionally, set a default alpha value (e.g., fully opaque)
886
+ alpha = Image.new('L', rgba_image.size, 255) # 255 for full opacity
887
+ rgba_image.putalpha(alpha)
888
+ return rgba_image
889
 
890
  # Example usage
891
  # convert_jpg_to_rgba('input.jpg', 'output.png')
 
911
 
912
  # Check if the input file exists
913
  if not input_path.exists():
914
+ #if file was renamed to lower case, update the input path
915
+ input_path = output_path
916
+ if not input_path.exists():
917
+ raise FileNotFoundError(f"The file {input_path} does not exist.")
918
 
919
  # Check file extension first to skip unnecessary processing
920
  if input_path.suffix.lower() not in ('.jpg', '.jpeg'):
921
  print(f"Skipping conversion: {input_path} is not a JPG or JPEG file.")
922
+ return None, None
923
 
924
  print(f"Converting to PNG: {input_path} is a JPG or JPEG file.")
925
 
 
967
  img = open_image(file_path)
968
  print(f"Opened image: {file_path}\n")
969
  # Handle ICO files
970
+ if file_path.lower().endswith(('.ico','.webp','.gif')):
971
  rgba_img = img.convert('RGBA')
972
  new_file_path = Path(file_path).with_suffix('.png')
973
  rgba_img.save(new_file_path, format='PNG')
 
1039
  with Image.open(file_path) as img:
1040
  # Convert to RGB if needed (handles RGBA, CMYK, etc.)
1041
  if img.mode != 'RGB':
1042
+ img = img.convert('RGB')
1043
  # Calculate target height maintaining aspect ratio
1044
  original_width, original_height = img.size
1045
  aspect_ratio = original_height / original_width
1046
+ target_height = int(target_width * aspect_ratio)
1047
  # Resize using the reference function
1048
+ resized_img = resize_image_with_aspect_ratio(img, target_width, target_height)
1049
  # Create output filename
1050
+ output_filename = output_path / f"{file_prefix}{file_path.name.lower()}"
1051
  # Save the resized image
1052
+ resized_img.save(output_filename, quality=95)
1053
  successful += 1
1054
+ print(f"Successfully resized: {file_path.name.lower()}")
1055
  except Exception as e:
1056
  failed += 1
1057
+ print(f"Failed to resize {file_path.name.lower()}: {str(e)}")
1058
 
1059
  print(f"\nResizing complete. Successfully processed: {successful}, Failed: {failed}")
1060
  return successful, failed
 
1100
  for key, value in PRE_RENDERED_MAPS_JSON_LEVELS.items():
1101
  print(f" '{key}': {{'file': '{value['file']}', 'thumbnail': '{value['thumbnail']}', 'quality': {value['quality']}}},")
1102
  print("}")
1103
+
1104
+ def calculate_optimal_fill_dimensions(image: Image.Image):
1105
+ # Extract the original dimensions
1106
+ original_width, original_height = image.size
1107
+
1108
+ # Set constants
1109
+ MIN_ASPECT_RATIO = 9 / 16
1110
+ MAX_ASPECT_RATIO = 16 / 9
1111
+ FIXED_DIMENSION = 1024
1112
+
1113
+ # Calculate the aspect ratio of the original image
1114
+ original_aspect_ratio = original_width / original_height
1115
+
1116
+ # Determine which dimension to fix
1117
+ if original_aspect_ratio > 1: # Wider than tall
1118
+ width = FIXED_DIMENSION
1119
+ height = round(FIXED_DIMENSION / original_aspect_ratio)
1120
+ else: # Taller than wide
1121
+ height = FIXED_DIMENSION
1122
+ width = round(FIXED_DIMENSION * original_aspect_ratio)
1123
+
1124
+ # Ensure dimensions are multiples of 8
1125
+ width = (width // 8) * 8
1126
+ height = (height // 8) * 8
1127
+
1128
+ # Enforce aspect ratio limits
1129
+ calculated_aspect_ratio = width / height
1130
+ if calculated_aspect_ratio > MAX_ASPECT_RATIO:
1131
+ width = (height * MAX_ASPECT_RATIO // 8) * 8
1132
+ elif calculated_aspect_ratio < MIN_ASPECT_RATIO:
1133
+ height = (width / MIN_ASPECT_RATIO // 8) * 8
1134
+
1135
+ # Ensure width and height remain above the minimum dimensions
1136
+ width = max(width, 576) if width == FIXED_DIMENSION else width
1137
+ height = max(height, 576) if height == FIXED_DIMENSION else height
1138
+
1139
+ return width, height