CodeByMrFinchum/OptimaLab35
CodeByMrFinchum/OptimaLab35
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Feat: Added compatibility with optima35 v1.0

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Mr Finchum 2025-01-28 15:03:47 +00:00
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20
CHANGELOG.md
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@ -1,6 +1,20 @@
# Changelog
## 0.4.x
### 0.4.0
- Fixed a critical issue that prevented the program from functioning.
- Updated compatibility to align with the **upcoming** optima35 **release**.
**Removal of TUI:**
- The TUI version is no longer compatible with optima35 v1.0.
- Maintaining two UIs has become too time-consuming, as the primary focus is on the GUI, which provides the best user experience. Recently, the TUI version was only receiving patches without any meaningful enhancements.
---
## 0.3.x
### 0.3.7: prepear for optima35 release
- Added a maximum version of dependencies list.
### 0.3.6: Patch
- Added check if any exif options are empty.
- Also made the exif editor aviable without checking the exif box.
@ -14,6 +28,8 @@
### 0.3.0
- Repo only: adding pipeline
---
## 0.2.x
### 0.2.3
- Refactored code for improved readability.
@ -34,6 +50,8 @@
- Added a new experimental preview window to display an image and show how changing values affects it.
- Programm now warns for potential overwrite of existing files.
---
## 0.1.x
### 0.1.1
- Update metadata, preview, readme, bump in version for pip
@ -41,6 +59,8 @@
### 0.1.0
- Preserved the current working GUI by pinning `optima35` to a specific version for guaranteed compatibility.
---
## 0.0.x
### 0.0.4-a2
- Adding __version__ to `__init__.py` so version is automaticly updated in program as well as pypi.

84
README.md
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@ -1,36 +1,56 @@
# **OptimaLab35**
[OptimaLab35](https://gitlab.com/CodeByMrFinchum/OptimaLab35) is a graphical and terminal user interface for [optima35](https://gitlab.com/CodeByMrFinchum/optima35). It is under **heavy development**, and both UI elements and cross-platform compatibility may change.
_Last updated: 28 Jan 2025_
## **Overview**
**OptimaLab35** extends **OPTIMA35** (**Organizing, Processing, Tweaking Images, and Modifying scanned Analogs from 35mm Film**) by providing an intuitive interface for image and metadata management. While tailored for analog photography, it supports any type of image.
**OptimaLab35** enhances **OPTIMA35** (**Organizing, Processing, Tweaking Images, and Modifying scanned Analogs from 35mm Film**) by offering a user-friendly graphical interface for efficient image and metadata management.
It serves as a GUI for the [OPTIMA35 library](https://gitlab.com/CodeByMrFinchum/optima35), providing an intuitive way to interact with the core functionalities.
---
## **Current Status**
### **Alpha Stage**
### **Versioning and Compatibility**
OptimaLab35 is built using **PySide6** and **Qt**, offering a modern and flexible interface for **OPTIMA35**.
The preserved version **v0.1.0** ensures stability with the current GUI design. It depends on **optima35==0.6.4**, a version confirmed to work seamlessly with this release. Future updates may introduce breaking changes, especially as the project evolves across platforms.
The program is under **active development**, and while versions released on PyPI should not contain major bugs, occasional issues may arise.
### **Installation**
For the most accurate and detailed update information, please refer to the well-maintained [**CHANGELOG**](https://gitlab.com/CodeByMrFinchum/OptimaLab35/-/blob/main/CHANGELOG.md), as this README may occasionally lag behind the latest updates.
Install via pip (dependencies are automatically managed, except for `simple-term-menu` used in TUI mode, which is Linux-only):
---
## **Features**
### **Image Processing**
- Resize images (upscale or downscale)
- Convert images to grayscale
- Adjust brightness and contrast
- Add customizable text-based watermarks
### **Image preview**
- Load a single image and see how change in brightness and contrast changes the image
### **EXIF Management**
- Add EXIF data using a simple dictionary
- Copy EXIF data from the original image
- Remove EXIF metadata completely
- Add timestamps (e.g., original photo timestamp)
- Automatically adjust EXIF timestamps based on image file names
- Add GPS coordinates to images
---
## **Installation**
Install via **pip** (dependencies are handled automatically):
```bash
pip install OptimaLab35
```
## **Development and Notes**
---
**Alpha Stage**
- UI designs (GUI and TUI) are evolving, and breaking changes may occur.
- The [**CHANGELOG**](https://gitlab.com/CodeByMrFinchum/OptimaLab35/-/blob/main/CHANGELOG.md) provides detailed updates.
- Some safety checks are still under development.
**Modes:**
- **GUI**: Default if **PySide6** is available.
- **TUI**: Fallback if **PySide6** is missing or can be explicitly started using the `--tui` flag.
### Preview GUI
## Preview GUI
**PREVIEW** might be out of date.
**Main tab**
@ -49,35 +69,7 @@ pip install OptimaLab35
![main](https://gitlab.com/CodeByMrFinchum/OptimaLab35/-/raw/main/media/exif_editor.png){width=40%}
**Info window**
![main](https://gitlab.com/CodeByMrFinchum/OptimaLab35/-/raw/main/media/info_window.png){width=40%}
## **Features**
### **Image Processing**
- Resizing
- Renaming with custom order
- Grayscale conversion
- Brightness and contrast adjustment
### **EXIF Management**
- Copy or add custom EXIF data
- Add GPS coordinates
- Add or modify EXIF dates
- Remove EXIF metadata
### **Watermarking**
- Add customizable watermarks
## **Dependencies**
**GUI Mode:**
- `optima35`
- `pyside6`
**TUI Mode (Linux only):**
- `simple-term-menu`
---
# Use of LLMs
In the interest of transparency, I disclose that Generative AI (GAI) large language models (LLMs), including OpenAI’s ChatGPT and Ollama models (e.g., OpenCoder and Qwen2.5-coder), have been used to assist in this project.

4
pyproject.toml
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@ -9,7 +9,7 @@ authors = [{ name = "Mr. Finchum" }]
description = "User interface for optima35."
readme = "pip_README.md"
requires-python = ">=3.8"
dependencies = ["optima35>=0.6.7", "pyside6", "PyYAML", "packaging"]
dependencies = ["optima35>=1.0.0, <2.0.0", "pyside6", "PyYAML"]
classifiers = [
"Programming Language :: Python :: 3",
"License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)",
@ -20,7 +20,7 @@ classifiers = [
Source = "https://gitlab.com/CodeByMrFinchum/OptimaLab35"
[project.scripts]
OptimaLab35 = "OptimaLab35.main:main"
OptimaLab35 = "OptimaLab35.__main__:main"
[tool.hatch.build.targets.wheel]
packages = ["src/OptimaLab35"]

7
src/OptimaLab35/__main__.py Normal file
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@ -0,0 +1,7 @@
from OptimaLab35 import gui, __version__
def main():
gui.main()
if __name__ == "__main__":
main()

19
src/OptimaLab35/gui.py
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@ -296,7 +296,6 @@ class OptimaLab35(QMainWindow, Ui_MainWindow):
def start_process(self):
self.toggle_buttons(False)
u = self.update_settings()
print(f"u in startinset_xif: {u}")
if u != None: # Get all user selected data
QMessageBox.warning(self, "Warning", f"Error: {u}")
self.toggle_buttons(True)
@ -321,7 +320,7 @@ class OptimaLab35(QMainWindow, Ui_MainWindow):
input_path = os.path.join(input_folder, image_file)
self.o.insert_dict_to_image(
self.o.insert_exif_to_image(
exif_dict = self.settings["user_selected_exif"],
image_path = input_path,
gps = self.settings["gps"])
@ -334,7 +333,6 @@ class OptimaLab35(QMainWindow, Ui_MainWindow):
def startinsert_exif(self):
self.toggle_buttons(False)
u = self.update_settings()
print(f"u in startinset_xif: {u}")
if u != None: # Get all user selected data
QMessageBox.warning(self, "Warning", f"Error: {u}")
self.toggle_buttons(True)
@ -435,9 +433,10 @@ class OptimaLab35(QMainWindow, Ui_MainWindow):
self.settings["user_selected_exif"] = None
self.settings["gps"] = None
u = self.check_selected_exif(self.settings["user_selected_exif"])
if u != True:
return u
if self.settings["user_selected_exif"] is not None:
u = self.check_selected_exif(self.settings["user_selected_exif"])
if u != True:
return u
# Helper functions, low level
def handle_exif_file(self, do):
@ -476,10 +475,10 @@ class PreviewWindow(QMainWindow, Ui_Preview_Window):
if not os.path.isfile(path):
return
try:
img = self.o.process_image(
save = False,
img = self.o.process_image_object(
image_input_file = path,
image_output_file = "",
resize = 50,
watermark = "PREVIEW",
grayscale = self.ui.grayscale_checkBox.isChecked(),
brightness = int(self.ui.brightness_spinBox.text()),
contrast = int(self.ui.contrast_spinBox.text())
@ -526,7 +525,7 @@ class ImageProcessorRunnable(QRunnable):
image_name = os.path.splitext(image_file)[0]
output_path = os.path.join(output_folder, image_name)
self.o.process_image(
self.o.process_and_save_image(
image_input_file = input_path,
image_output_file = output_path,
file_type = self.settings["file_format"],

54
src/OptimaLab35/main.py
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@ -1,54 +0,0 @@
import os
from argparse import ArgumentParser
from OptimaLab35 import gui, __version__
# Try importing TUI only if simple-term-menu is installed
try:
from OptimaLab35 import tui
simple_term_menu_installed = True
except ImportError:
simple_term_menu_installed = False
# Check if PySide is installed
def check_pyside_installed():
try:
import PySide6 # Replace with PySide2 if using that version
return True
except ImportError:
return False
def start_gui():
gui.main()
def start_tui():
if simple_term_menu_installed:
tui.main()
else:
print("Error: simple-term-menu is not installed. Please install it to use the TUI mode.")
exit(1)
def main():
parser = ArgumentParser(description="Start the Optima35 application.")
parser.add_argument("--tui", action="store_true", help="Start in terminal UI mode.")
args = parser.parse_args()
if args.tui:
print("Starting TUI...")
start_tui()
return
# Check OS and start GUI if on Windows
if os.name == "nt":
print("Detected Windows. Starting GUI...")
start_gui()
else:
# Non-Windows: Check if PySide is installed
if check_pyside_installed():
print("PySide detected. Starting GUI...")
start_gui()
else:
print("PySide is not installed. Falling back to TUI...")
start_tui()
if __name__ == "__main__":
main()

330
src/OptimaLab35/tui.py
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@ -1,330 +0,0 @@
import os
from datetime import datetime
# my packages
from optima35.core import OptimaManager
from OptimaLab35.utils.utility import Utilities
from OptimaLab35.ui.simple_tui import SimpleTUI
from OptimaLab35 import __version__
class OptimaLab35_lite():
def __init__(self):
self.name = "OptimaLab35-lite"
self.version = __version__
self.o = OptimaManager()
self.u = Utilities()
self.tui = SimpleTUI()
self.u.program_configs()
self.exif_file = os.path.expanduser("~/.config/OptimaLab35/exif.yaml")
self.available_exif_data = self.u.read_yaml(self.exif_file)
self.setting_file = os.path.expanduser("~/.config/OptimaLab35/tui_settings.yaml")
self.settings = {
"input_folder": None,
"output_folder": None,
"file_format": None,
"resize": None,
"copy_exif": None,
"contrast": None,
"brightness": None,
"new_file_names": None,
"invert_image_order": False,
"watermark": None,
"gps": None,
"modifications": [],
}
self.settings_to_save = [
"resize",
"jpg_quality",
"png_compression",
"optimize",
"contrast",
"brightness"
]
def _process(self):
self._check_options() # Get all user selected data
input_folder_valid = os.path.exists(self.settings["input_folder"])
output_folder_valid = os.path.exists(self.settings["output_folder"])
if not input_folder_valid or not output_folder_valid:
print("Warning", f"Input location {input_folder_valid}\nOutput folder {output_folder_valid}...")
return
input_folder = self.settings["input_folder"]
output_folder = self.settings["output_folder"]
image_files = [
f for f in os.listdir(input_folder) if f.lower().endswith((".png", ".jpg", ".jpeg", ".webp"))
]
i = 1
for image_file in image_files:
input_path = os.path.join(input_folder, image_file)
if self.settings["new_file_names"] != False:
image_name = self.u.append_number_to_name(self.settings["new_file_names"], i, len(image_files), self.settings["invert_image_order"])
else:
image_name = os.path.splitext(image_file)[0]
output_path = os.path.join(output_folder, image_name)
self.o.process_image(
image_input_file = input_path,
image_output_file = output_path,
file_type = self.settings["file_format"],
quality = self.settings["jpg_quality"],
compressing = self.settings["png_compression"],
optimize = self.settings["optimize"],
resize = self.settings["resize"],
watermark = self.settings["watermark"],
font_size = self.settings["font_size"],
grayscale = self.settings["grayscale"],
brightness = self.settings["brightness"],
contrast = self.settings["contrast"],
dict_for_exif = self.selected_exif,
gps = self.settings["gps"],
copy_exif = self.settings["copy_exif"])
self.u.progress_bar(i, len(image_files))
i += 1
def _check_options(self):
try:
if "Resize image" in self.settings["modifications"]:
self.settings["resize"] = self.settings["resize"]
else:
self.settings["resize"] = None
if "Convert to grayscale" in self.settings["modifications"]:
self.settings["grayscale"] = True
else:
self.settings["grayscale"] = False
if "Change contrast" in self.settings["modifications"]:
self.settings["contrast"] = self.settings["contrast"]
else:
self.settings["contrast"] = None
if "Change brightness" in self.settings["modifications"]:
self.settings["brightness"] = self.settings["brightness"]
else:
self.settings["brightness"] = None
if "Rename images" in self.settings["modifications"]:
self.settings["new_file_names"] = self.settings["new_file_names"]
else:
self.settings["new_file_names"] = False
if "Invert image order" in self.settings["modifications"]:
self.settings["invert_image_order"] = True
else:
self.settings["invert_image_order"] = False
if "Add Watermark" in self.settings["modifications"]:
self.settings["watermark"] = self.settings["watermark"]
else:
self.settings["watermark"] = None
self.settings["optimize"] = self.settings["optimize"]
self.settings["png_compression"] = self.settings["png_compression"]
self.settings["jpg_quality"] = self.settings["jpg_quality"]
self.settings["input_folder"] = self.settings["input_folder"]
self.settings["output_folder"] = self.settings["output_folder"]
self.settings["file_format"] = self.settings["file_format"]
self.settings["font_size"] = 2 # need to add option to select size
self.settings["copy_exif"] = self.settings["copy_exif"]
if "Change EXIF" in self.settings["modifications"]: #missing
self.selected_exif = self._collect_exif_data() #
else:
self.selected_exif = None
except Exception as e:
print(f"Whoops: {e}")
def _load_or_ask_settings(self):
"""Load settings from a YAML file or ask the user if not present or incomplete."""
try:
if self._read_settings(self.settings_to_save):
for item in self.settings_to_save:
print(f"{item}: {self.settings[item]}")
use_saved = self.tui.yes_no_menu("Use these settings?")
if use_saved:
return
else:
print("No settings found...")
self._ask_for_settings()
except Exception as e:
print(f"Error: {e}")
self._ask_for_settings()
def _ask_for_settings(self):
print("Asking for new settings...\n")
print(f"Settings for {self.name} v{self.version} will be saved {self.setting_file}...")
self.settings["resize"] = self.take_input_and_validate(question = "Default resize percentage (below 100 downscale, above upscale): ", accepted_type = int, min_value = 10, max_value = 200)
self.settings["contrast"] = self.take_input_and_validate(question = "Default contrast percentage (negative = decrease, positive = increase): ", accepted_type = int, min_value = -100, max_value = 100)
self.settings["brightness"] = self.take_input_and_validate(question = "Default brighness percentage (negative = decrease, positive = increase): ", accepted_type = int, min_value = -100, max_value = 100)
self.settings["jpg_quality"] = self.take_input_and_validate(question = "JPEG quality (1-100, 80 default): ", accepted_type = int, min_value = 1, max_value = 100)
self.settings["png_compression"] = self.take_input_and_validate(question = "PNG compression level (0-9, 6 default): ", accepted_type = int, min_value = 0, max_value = 9)
self.settings["optimize"] = self.tui.yes_no_menu("Optimize images i.e. compressing?")
self._write_settings(self.settings_to_save)
def _write_settings(self, keys_to_save):
""""Write self.setting, but only specific values"""
keys = keys_to_save
filtered_settings = {key: self.settings[key] for key in keys if key in self.settings}
self.u.write_yaml(self.setting_file, filtered_settings)
print("New settings saved successfully.")
def _read_settings(self, keys_to_load):
"""
Read settings from the settings file and update self.settings
with the values for specific keys without overwriting existing values.
"""
# First draft by ChatGPT, adjusted to fit my needs.
keys = keys_to_load
if os.path.exists(self.setting_file):
loaded_settings = self.u.read_yaml(self.setting_file)
for key in keys:
if key in loaded_settings:
self.settings[key] = loaded_settings[key]
print("Settings loaded successfully.")
return True
else:
print("Settings file empty.")
return False
def _collect_exif_data(self):
"""Collect EXIF data based on user input."""
print(f"Exif file can be found {self.exif_file}...")
user_data = {}
fields = [
"make", "model", "lens", "iso", "image_description",
"user_comment", "artist", "copyright_info"
]
for field in fields:
choise = self.tui.choose_menu(f"Enter {field.replace('_', ' ').title()}", self.available_exif_data[field])
user_data[field] = choise
user_data["software"] = f"{self.o.name} {self.o.version}"
new_date = self._get_date_input()
if new_date:
user_data["date_time_original"] = new_date
self.settings["gps"] = self._get_gps_input(user_data)
return user_data
def _get_gps_input(self, test_exif):
while True:
lat = input("Enter Latitude (xx.xxxxxx): ")
if lat == "":
return None
long = input("Enter Longitude (xx.xxxxxx): ")
try:
self.o.exif_handler.add_geolocation_to_exif(test_exif, float(lat), float(long))
return [float(lat), float(long)]
except Exception:
print("Invalid GPS formate, try again...")
def _get_date_input(self):
# Partially chatGPT
while True:
date_input = input("Enter a date (yyyy-mm-dd): ")
if date_input == "":
return None # Skip if input is empty
try:
new_date = datetime.strptime(date_input, "%Y-%m-%d")
return new_date.strftime("%Y:%m:%d 00:00:00")
except ValueError:
print("Invalid date format. Please enter the date in yyyy-mm-dd format.")
def _get_user_settings(self):
"""Get initial settings from the user."""
menu_options = [
"Resize image",
"Change EXIF",
"Convert to grayscale",
"Change contrast",
"Change brightness",
"Rename images",
"Invert image order",
"Add Watermark"
] # new option can be added here.
self.settings["input_folder"] = input("Enter path of input folder: ").strip() # Add: check if folder exists.
self.settings["output_folder"] = input("Enter path of output folder: ").strip()
self.settings["file_format"] = self.take_input_and_validate(question = "Enter export file format (jpg, png, webp): ", accepted_input = ["jpg", "png", "webp"], accepted_type = str)
self.settings["modifications"] = self.tui.multi_select_menu(
f"\n{self.name} v{self.version} for {self.o.name} v.{self.o.version} \nSelect what you want to do (esc or q to exit)",
menu_options
)
if "Change EXIF" not in self.settings["modifications"]:
self.settings["copy_exif"] = self.tui.yes_no_menu("Do you want to copy exif info from original file?")
if "Rename images" in self.settings["modifications"]:
self.settings["new_file_names"] = input("What should be the name for the new images? ") # Need
else:
self.settings["new_file_names"] = False
if "Invert image order" in self.settings["modifications"]:
self.settings["invert_image_order"] = True
else:
self.settings["invert_image_order"] = False
if "Add Watermark" in self.settings["modifications"]:
self.settings["watermark"] = input("Enter text for watermark. ")
else:
self.settings["watermark"] = False
os.makedirs(self.settings["output_folder"], exist_ok = True)
def take_input_and_validate(self, question, accepted_input = None, accepted_type = str, min_value = None, max_value = None):
"""
Asks the user a question, validates the input, and ensures it matches the specified criteria.
Args:
question (str): The question to ask the user.
accepted_input (list): A list of acceptable inputs (optional for non-numeric types).
accepted_type (type): The expected type of input (e.g., str, int, float).
min_value (int/float): Minimum value for numeric inputs (optional).
max_value (int/float): Maximum value for numeric inputs (optional).
Returns:
The validated user input.
"""
# Main layout by chatGPT, but modified.
while True:
user_input = input(question).strip()
try:
# Convert input to the desired type
if accepted_type in [int, float]:
user_input = accepted_type(user_input)
# Validate range for numeric types
if (min_value is not None and user_input < min_value) or (max_value is not None and user_input > max_value):
print(f"Input must be between {min_value} and {max_value}.")
continue
elif accepted_type == str:
# No conversion needed for strings
user_input = str(user_input)
else:
raise ValueError(f"Unsupported type: {accepted_type}")
# Validate against accepted inputs if provided
if accepted_input is not None and user_input not in accepted_input:
print(f"Invalid input. Must be one of: {', '.join(map(str, accepted_input))}.")
continue
return user_input # Input is valid
except ValueError:
print(f"Invalid input. Must be of type {accepted_type.__name__}.")
def run(self):
"""Run the main program."""
self._load_or_ask_settings()
self._get_user_settings()
self._process()
print("Done")
def main():
app = OptimaLab35_lite()
app.run()
if __name__ == "__main__":
main()