compatibiliy with windows paths and cr3 image format

doc/conf.py

@@ -40,6 +40,7 @@
     "exifread",
     "rawpy",
     "opencv-python",
+    "hachoir"
 ]
 
 

ledsa/core/ConfigData.py

@@ -1,3 +1,4 @@
+import os
 import configparser as cp
 from datetime import datetime, timedelta
 
@@ -271,10 +272,15 @@ def in_time_diff_to_img_time(self) -> None:
             time = input('Please give the time shown on the clock in the time reference image in hh:mm:ss: ')
             self['DEFAULT']['time_ref_img_time'] = str(time)
         time = self['DEFAULT']['time_ref_img_time']
-        print(self['DEFAULT']['img_directory'] + self['DEFAULT']['time_img_id'])
-        tag = 'EXIF DateTimeOriginal'
-        exif_entry = get_exif_entry(self['DEFAULT']['img_directory'] + self['DEFAULT']['img_name_string'].format(
-            self['DEFAULT']['time_img_id']), tag)
+        print(os.path.join(self['DEFAULT']['img_directory'], self['DEFAULT']['img_name_string'].format(
+            self['DEFAULT']['time_img_id'])))
+        if '.CR3' in os.path.join(self['DEFAULT']['img_directory'], self['DEFAULT']['img_name_string'].format(
+            self['DEFAULT']['time_img_id'])):
+            tag = 'Creation date'
+        else:
+            tag = 'EXIF DateTimeOriginal'
+        exif_entry = get_exif_entry(os.path.join(self['DEFAULT']['img_directory'], self['DEFAULT']['img_name_string'].format(
+            self['DEFAULT']['time_img_id'])), tag)
         date, time_meta = exif_entry.split(' ')
         self['DEFAULT']['date'] = date
         img_time = _get_datetime_from_str(date, time_meta)
@@ -351,8 +357,13 @@ def get_start_time(self) -> None:
         Updates the 'DEFAULT' key with the 'start_time' computed.
 
         """
-        exif_entry = get_exif_entry(self['DEFAULT']['img_directory'] + self['DEFAULT']['img_name_string'].format(
-            self['DEFAULT']['first_img_experiment_id']), 'EXIF DateTimeOriginal')
+        if '.CR3' in os.path.join(self['DEFAULT']['img_directory'], self['DEFAULT']['img_name_string'].format(
+            self['DEFAULT']['first_img_experiment_id'])):
+            tag = 'Creation date'
+        else:
+            tag = 'EXIF DateTimeOriginal'
+        exif_entry = get_exif_entry(os.path.join(self['DEFAULT']['img_directory'], self['DEFAULT']['img_name_string'].format(
+            self['DEFAULT']['first_img_experiment_id'])), tag)
         date, time_meta = exif_entry.split(' ')
         time_img = _get_datetime_from_str(date, time_meta)
         start_time = time_img - timedelta(seconds=self['DEFAULT'].getint('exif_time_infront_real_time'))
@@ -366,6 +377,7 @@ def _get_datetime_from_str(date: str, time: str) -> datetime:
     The function can handle two formats:
     1. '%Y:%m:%d %H:%M:%S' - standard format with colons in the date.
     2. '%d.%m.%Y %H:%M:%S' - format with periods in the date.
+    3. '%d-%m-%Y %H:%M:%S' - format with hyphens in the date.
 
     :param date: The date string.
     :type date: str
@@ -376,6 +388,8 @@ def _get_datetime_from_str(date: str, time: str) -> datetime:
     """
     if date.find(":") != -1:
         date_time = datetime.strptime(date + ' ' + time, '%Y:%m:%d %H:%M:%S')
+    elif date.find("-") != -1:
+        date_time = datetime.strptime(date + ' ' + time, '%Y-%m-%d %H:%M:%S')
     else:
         date_time = datetime.strptime(date + ' ' + time, '%d.%m.%Y %H:%M:%S')
     return date_time

ledsa/core/image_reading.py

@@ -1,5 +1,7 @@
 import os
-
+from hachoir.parser import createParser
+from hachoir.metadata import extractMetadata
+from pathlib import Path
 import exifread
 import numpy as np
 import rawpy
@@ -22,7 +24,7 @@ def read_channel_data_from_img(filename: str, channel: int) -> np.ndarray:
     extension = os.path.splitext(filename)[-1]
     if extension in ['.JPG', '.JPEG', '.jpg', '.jpeg', '.PNG', '.png']:
         channel_array = _read_channel_data_from_img_file(filename, channel)
-    elif extension in ['.CR2']:
+    elif extension in ['.CR2','.CR3','.NEF','.ARW','.DNG']:
         channel_array = _read_channel_data_from_raw_file(filename, channel)
     return channel_array
 
@@ -91,6 +93,25 @@ def get_exif_entry(filename: str, tag: str) -> str:
     :rtype: str
     :raises KeyError: If the EXIF tag is not found in the image metadata.
     """
+
+    #Read Metadata CR3 (! ISO, Blende und Verschlusszeit kann durch diese Methode nicht ausgegeben werden)
+    if '.CR3' in filename:
+        parser = createParser(str(filename))
+        if not parser:
+            raise ValueError(f"Konnte Datei nicht parsen: {filename}")
+
+        metadata = extractMetadata(parser)
+        if not metadata:
+            raise ValueError("Keine Metadaten gefunden.")
+
+        try:
+            for line in metadata.exportPlaintext():
+                if tag in line:
+                    return line.split(":", 1)[1].strip()
+        except:
+            print("Keine Aufnahmezeit gefunden.")
+            exit(1)
+
     with open(filename, 'rb') as f:
         exif = exifread.process_file(f, details=False, stop_tag=tag)
     try:

ledsa/data_extraction/init_functions.py

@@ -92,7 +92,7 @@ def generate_image_infos_csv(config: ConfigData, build_experiment_infos=False, b
             _save_analysis_infos(img_data)
 
 
-def _calc_experiment_and_real_time(build_type: str, config: ConfigData, tag: str, img_number: int) -> None:
+def _calc_experiment_and_real_time(build_type: str, config: ConfigData, tag: str, img_number: str) -> None:
     """
     Calculate experiment and real-time based on image metadata and config settings.
 
@@ -107,8 +107,8 @@ def _calc_experiment_and_real_time(build_type: str, config: ConfigData, tag: str
     :return: Tuple containing experiment time and real time.
     :rtype: tuple
     """
-    exif_entry = get_exif_entry(config['DEFAULT']['img_directory'] +
-                                config['DEFAULT']['img_name_string'].format(int(img_number)), tag)
+    exif_entry = get_exif_entry(os.path.join(config['DEFAULT']['img_directory'],
+                                config['DEFAULT']['img_name_string'].format(img_number)), tag)
     date, time_meta = exif_entry.split(' ')
     date_time_img = _get_datetime_from_str(date, time_meta)
 
@@ -125,7 +125,7 @@ def _get_datetime_from_str(date: str, time: str) -> datetime:
     """
     Convert date and time strings to a datetime object.
 
-    :param date: Date string in the format '%Y:%m:%d' or '%d.%m.%Y'.
+    :param date: Date string in the format '%Y:%m:%d' or '%d.%m.%Y' or '%Y-%m-%d'.
     :type date: str
     :param time: Time string in the format '%H:%M:%S'.
     :type time: str
@@ -134,6 +134,8 @@ def _get_datetime_from_str(date: str, time: str) -> datetime:
     """
     if date.find(":") != -1:
         date_time = datetime.strptime(date + ' ' + time, '%Y:%m:%d %H:%M:%S')
+    elif date.find("-") != -1:
+        date_time = datetime.strptime(date + ' ' + time, '%Y-%m-%d %H:%M:%S')
     else:
         date_time = datetime.strptime(date + ' ' + time, '%d.%m.%Y %H:%M:%S')
     return date_time
@@ -193,9 +195,12 @@ def _build_img_data_string(build_type: str, config: ConfigData) -> str:
     img_increment = config.getint(build_type, 'num_skip_imgs') + 1 if build_type == 'analyse_photo' else 1
     img_id_list = _find_img_number_list(first_img_id, last_img_id, img_increment)
     for img_id in img_id_list:
-        tag = 'EXIF DateTimeOriginal'
+        if '.CR3' in config['DEFAULT']['img_name_string']:
+            tag = 'Creation date'
+        else:
+            tag = 'EXIF DateTimeOriginal'
         experiment_time, time = _calc_experiment_and_real_time(build_type, config, tag, img_id)
-        img_data += (str(img_idx) + ',' + config[build_type]['img_name_string'].format(int(img_id)) +
+        img_data += (str(img_idx) + ',' + config[build_type]['img_name_string'].format(img_id) +
                      ',' + time.strftime('%H:%M:%S') + ',' + str(experiment_time) + '\n')
         img_idx += 1
     return img_data

ledsa/data_extraction/step_3_functions.py

@@ -58,7 +58,7 @@ def generate_analysis_data(img_filename: str, channel: int, search_areas: np.nda
     return img_analysis_data
 
 
-def create_fit_result_file(img_data: List[LEDAnalysisData], img_id: int, channel: int) -> None: # TODO: rename because misleading
+def create_fit_result_file(img_data: List[LEDAnalysisData], img_id: str, channel: int) -> None: # TODO: rename because misleading
     """
       Create a result file for a single image, containing the pixel values and, if applicable, the fit results of all LEDs.
 

ledsa/tools/exposure_checker.ipynb

@@ -1,64 +1,73 @@
 {
  "cells": [
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "id": "d5b8be1e27d27315",
+   "metadata": {},
    "source": [
     "# Image Exposure Checker\n",
     "\n",
-    "This notebook allows you to check the exposure of a series of pictures. It calculates the pixel saturation value as a percentage.\n"
-   ],
-   "id": "d5b8be1e27d27315"
+    "This notebook allows you to check the exposure of a series of pictures. It calculates the pixel saturation value as a percentage.\n",
+    "\n",
+    "Does not work for Images in CR3 format.\n"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
-   "source": "# Dependencies\n",
-   "id": "9df8a44a552be70"
+   "id": "9df8a44a552be70",
+   "metadata": {},
+   "source": [
+    "# Dependencies\n"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "41c98f47ba1f266f",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import os\n",
     "from ledsa.core.image_reading import read_channel_data_from_img, get_exif_entry"
-   ],
-   "id": "41c98f47ba1f266f"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
-   "source": "# Configuration\n",
-   "id": "8bab111a65dd1b89"
+   "id": "8bab111a65dd1b89",
+   "metadata": {},
+   "source": [
+    "# Configuration\n"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "aa799b526e7eb076",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# Configure the image path and range\n",
     "image_dir = \"/path/to/your/images\"  # Update this to your image directory\n",
     "image_name_string = \"IMG_{:04d}.JPG\"  # F-string template for image names\n",
     "image_range = range(1, 10)  # Range of image numbers to process\n",
     "channel = 0  # Color channel to analyze (0=Red, 1=Green, 2=Blue)\n",
     "saturation = 255"
-   ],
-   "id": "aa799b526e7eb076"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
-   "source": "# Process Images\n",
-   "id": "9b3295c6d521431e"
+   "id": "9b3295c6d521431e",
+   "metadata": {},
+   "source": [
+    "# Process Images\n"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "344c5f7ce039571b",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# Process each image in the range\n",
     "for img_id in image_range:\n",
@@ -89,11 +98,14 @@
     "\n",
     "        \n",
     "\n"
-   ],
-   "id": "344c5f7ce039571b"
+   ]
   }
  ],
- "metadata": {},
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }

ledsa/tools/photo_renamer.py

@@ -6,6 +6,7 @@
 import pandas as pd
 import exifread
 
+#does not work for Images in CR3 format
 
 def set_working_dir():
     """