Release candidate
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parent
8f539d4097
commit
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4 changed files with 175 additions and 82 deletions
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@ -26,7 +26,7 @@ build:
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- job: gitversion
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artifacts: true
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script:
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- sed -i "s/0.0.1/${GitVersion_MajorMinorPatch}/" src/optima35/__init__.py
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- sed -i "s/1.0.0/${GitVersion_MajorMinorPatch}/" src/optima35/__init__.py
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- cat src/optima35/__init__.py
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- python3 -m pip install build
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- python3 -m build
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@ -1,5 +1,10 @@
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# Changelog
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## 1.0.0-rc:
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### Refactoring
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- Added function descriptions for better clarity and maintainability.
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- Introduced guidelines for each function, defining objectives and expected behavior.
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## 0.12.x
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### 0.12.2: Bug fixes
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- Fixed missing lens in meta data
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@ -1 +1 @@
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__version__ = "0.0.1"
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__version__ = "1.0.0"
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@ -22,83 +22,124 @@ class OptimaManager:
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data_for_exif["date_time_original"] = new_time.strftime("%Y:%m:%d %H:%M:%S")
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return data_for_exif
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def process_image(self, # TODO: split into two classes, one for modification for one saving..
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image_input_file,
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image_output_file,
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file_type = "jpg",
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quality = 90,
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compressing = 6,
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optimize = False,
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resize = None,
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watermark = None,
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font_size = 2,
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grayscale = False,
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brightness = None,
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contrast = None,
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dict_for_exif = None,
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gps = None,
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copy_exif = False,
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save = True):
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# Partly optimized by ChatGPT
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# Open the image file
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with self.image_processor.open_image(image_input_file) as img:
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processed_img = img
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image_name = os.path.basename(image_output_file) # for date adjustment
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# Resize
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def _process_image(
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self,
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image_input_file: str,
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resize: int = None,
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watermark: str = None,
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font_size: int = 2,
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grayscale: bool = False,
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brightness: float = None,
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contrast: float = None
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):
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# Restructured by ChatGPT, but had to fix bugs
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img = self.image_processor.open_image(image_input_file)
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# Apply transformations
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if resize is not None:
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processed_img = self.image_processor.resize_image(
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image=processed_img, percent = resize
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)
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# Watermark
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print("Resize")
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img = self.image_processor.resize_image(img, percent=resize)
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if watermark is not None:
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processed_img = self.image_processor.add_watermark(
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processed_img, watermark, int(font_size)
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)
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# Grayscale
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print("Watermark")
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img = self.image_processor.add_watermark(img, watermark, font_size)
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if grayscale:
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processed_img = self.image_processor.grayscale(processed_img)
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# Brightness
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print("Grayscale")
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img = self.image_processor.grayscale(img)
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if brightness is not None:
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processed_img = self.image_processor.change_brightness(
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processed_img, brightness
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)
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# Contrast
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print("Brightness")
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img = self.image_processor.change_brightness(img, brightness)
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if contrast is not None:
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processed_img = self.image_processor.change_contrast(
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processed_img, contrast
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)
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print("Contrast")
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img = self.image_processor.change_contrast(img, contrast)
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return img
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# EXIF data handling
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exif_piexif_format = None
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if dict_for_exif: # todo: maybe move to ui and only accept complete exif dicts..
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selected_exif = dict_for_exif
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def _handle_exif(
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self,
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image,
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file_name,
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dict_for_exif: dict = None,
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gps: tuple[float, float] = None,
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copy_exif: bool = False
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):
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# Restructured by ChatGPT, but had to fix bugs
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# Build or copy EXIF data
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if dict_for_exif:
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if "date_time_original" in dict_for_exif:
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selected_exif = self.modify_timestamp_in_exif(selected_exif, image_name)
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exif_piexif_format = self.exif_handler.build_exif_bytes(
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selected_exif, self.image_processor.get_image_size(processed_img)
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dict_for_exif = self.modify_timestamp_in_exif(dict_for_exif, file_name)
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exif_data = self.exif_handler.build_exif_bytes(
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dict_for_exif, self.image_processor.get_image_size(image)
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)
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if gps:
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exif_data = self.exif_handler.add_geolocation_to_exif(
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exif_data, gps[0], gps[1]
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)
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elif copy_exif:
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exif_data = self.exif_handler.get_exif_info(image)
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else:
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exif_data = None
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return exif_data
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def process_and_save_image(
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self,
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image_input_file: str,
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image_output_file: str,
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file_type: str = "jpg",
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quality: int = 90,
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compressing: int = 6,
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optimize: bool = False,
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resize: int = None,
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watermark: str = None,
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font_size: int = 2,
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grayscale: bool = False,
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brightness: float = None,
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contrast: float = None,
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dict_for_exif: dict = None,
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gps: tuple[float, float] = None,
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copy_exif: bool = False
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) -> None:
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"""
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Processes an image with the given parameters and saves the output to a file.
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Args:
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image_input_file (str): Path to the input image file.
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image_output_file (str): Path to save the processed image.
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file_type (str): Output image format ('jpg', 'png'). Defaults to 'jpg'.
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quality (int): JPEG quality (1-100). Defaults to 90.
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compressing (int): PNG compression level (0-9). Defaults to 6.
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optimize (bool): Optimize image for smaller file size. Defaults to False.
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resize (int, optional): Resize percentage. Defaults to None.
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watermark (str, optional): Watermark text to add. Defaults to None.
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font_size (int): Font size for the watermark. Defaults to 2.
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grayscale (bool): Convert image to grayscale. Defaults to False.
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brightness (float, optional): Adjust brightness (e.g., 1.2 for 20% brighter). Defaults to None.
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contrast (float, optional): Adjust contrast (e.g., 1.5 for 50% higher contrast). Defaults to None.
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dict_for_exif (dict, optional): EXIF metadata to insert. Defaults to None.
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gps (tuple[float, float], optional): GPS coordinates (latitude, longitude). Defaults to None.
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copy_exif (bool): Copy EXIF metadata from the input image. Defaults to False.
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Returns:
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None
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"""
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# Restructured by ChatGPT
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processed_img = self._process_image(
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image_input_file,
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resize,
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watermark,
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font_size,
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grayscale,
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brightness,
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contrast,
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)
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# GPS data
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if gps is not None:
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latitude = float(gps[0])
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longitude = float(gps[1])
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exif_piexif_format = self.exif_handler.add_geolocation_to_exif(exif_piexif_format, latitude, longitude)
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# Handle EXIF metadata
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exif_piexif_format = self._handle_exif(
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image = processed_img,
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file_name = image_output_file,
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dict_for_exif = dict_for_exif,
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gps = gps,
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copy_exif = copy_exif
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)
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# Copy EXIF data if selected, and ensure size is correct in exif data
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elif copy_exif:
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try:
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og_exif = self.exif_handler.get_exif_info(img)
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og_exif["Exif"][40962], og_exif["Exif"][40963] = self.image_processor.get_image_size(processed_img)
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exif_piexif_format = og_exif
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except Exception:
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print("Copying EXIF data selected, but no EXIF data is available in the original image file.")
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if save:
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# Save the processed image
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# Save the image
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self.image_processor.save_image(
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image = processed_img,
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path = image_output_file,
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@ -106,12 +147,59 @@ class OptimaManager:
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file_type = file_type,
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jpg_quality = quality,
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png_compressing = compressing,
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optimize = optimize
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optimize = optimize,
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)
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def process_image_object(
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self,
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image_input_file: str,
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resize: int = None,
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watermark: str = None,
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font_size: int = 2,
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grayscale: bool = False,
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brightness: float = None,
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contrast: float = None
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):
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"""
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Processes an image with the given parameters and returns the modified image object.
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Args:
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image_input_file (str): Path to the input image file.
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resize (int, optional): Resize percentage. Defaults to None.
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watermark (str, optional): Watermark text to add. Defaults to None.
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font_size (int): Font size for the watermark. Defaults to 2.
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grayscale (bool): Convert image to grayscale. Defaults to False.
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brightness (float, optional): Adjust brightness. Defaults to None.
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contrast (float, optional): Adjust contrast. Defaults to None.
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Returns:
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Image: The processed image object.
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"""
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# Restructured by ChatGPT
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processed_img = self._process_image(
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image_input_file,
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resize,
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watermark,
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font_size,
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grayscale,
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brightness,
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contrast,
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)
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else:
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return self.image_processor.convert_pil_to_qtimage(processed_img)
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def insert_dict_to_image(self, exif_dict, image_path, gps = None):
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def insert_exif_to_image(self, exif_dict: dict, image_path: str, gps: tuple[float, float] = None) -> None:
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"""
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Inserts EXIF metadata into an image.
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Args:
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exif_data (dict): A dictionary containing EXIF metadata as key-value pairs (e.g., strings, integers).
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image_path (str): Absolute path to the target image file.
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gps (tuple[float, float], optional): GPS coordinates as a tuple (latitude, longitude). Defaults to None.
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Returns:
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None: The function modifies the image file in place.
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"""
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# Restructured by ChatGPT
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image_name, ending = os.path.splitext(os.path.basename(image_path))
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img = self.image_processor.open_image(image_path)
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selected_exif = exif_dict
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