Qr/bar code detection

.gitignore

@@ -11,6 +11,10 @@ dist/
 06-Package
 *logs/
 _build/
+venv/
+.coverage
+coverage.lcov
+results/
 
 # Files
 *.pyc

Granny/Analyses/Analysis.py

@@ -136,6 +136,82 @@ def resetRetValues(self):
         """
         self.ret_values = {}
 
+    def _parse_qr_from_filename(self, filename: str) -> dict:
+        """
+        Extract QR code information from segmented image filename.
+
+        Expected format: PROJECT_LOT_DATE_VARIETY_fruit_##.png
+        Example: APPLE2025_LOT001_2025-12-02_BB-Late_fruit_01.png
+
+        Args:
+            filename: Image filename (with or without path)
+
+        Returns:
+            Dictionary with QR information:
+            {
+                'project': project code or empty string,
+                'lot': lot code or empty string,
+                'date': date string or empty string,
+                'variety': variety string or empty string
+            }
+
+        Notes:
+            - Returns empty strings for all fields if parsing fails
+            - Handles legacy filenames gracefully (no QR data)
+        """
+        import re
+        from pathlib import Path
+
+        # Extract just the filename without path
+        filename_only = Path(filename).name
+
+        # Pattern: PROJECT_LOT_DATE_VARIETY_fruit_##.png
+        # Use regex to match everything before "_fruit_##"
+        pattern = r'^(.+?)_(.+?)_(.+?)_(.+?)_fruit_\d+\.(?:png|jpg|jpeg)$'
+        match = re.match(pattern, filename_only)
+
+        if match:
+            return {
+                'project': match.group(1),
+                'lot': match.group(2),
+                'date': match.group(3),
+                'variety': match.group(4)
+            }
+        else:
+            # Parsing failed - return empty strings (no QR data)
+            return {
+                'project': '',
+                'lot': '',
+                'date': '',
+                'variety': ''
+            }
+
+    def _add_qr_metadata(self, result_img, filename: str):
+        """
+        Parse QR/barcode metadata from filename and add to result image.
+
+        Args:
+            result_img: Image instance to add metadata values to
+            filename: Image filename to parse
+        """
+        qr_info = self._parse_qr_from_filename(filename)
+        if qr_info['project']:
+            project_val = StringValue("project", "project", "Project code from QR code")
+            project_val.setValue(qr_info['project'])
+            result_img.addValue(project_val)
+
+            lot_val = StringValue("lot", "lot", "Lot code from QR code")
+            lot_val.setValue(qr_info['lot'])
+            result_img.addValue(lot_val)
+
+            date_val = StringValue("date", "date", "Date from QR code")
+            date_val.setValue(qr_info['date'])
+            result_img.addValue(date_val)
+
+            variety_val = StringValue("variety", "variety", "Variety from QR code")
+            variety_val.setValue(qr_info['variety'])
+            result_img.addValue(variety_val)
+
     def performAnalysis(self) -> List[Image]:
         """
         Once all required parameters have been set, this function is used

Granny/Analyses/BlushColor.py

@@ -25,6 +25,7 @@
 from Granny.Models.Values.ImageListValue import ImageListValue
 from Granny.Models.Values.IntValue import IntValue
 from Granny.Models.Values.MetaDataValue import MetaDataValue
+from Granny.Models.Values.StringValue import StringValue
 from numpy.typing import NDArray
 
 
@@ -266,6 +267,9 @@ def _processImage(self, image_instance: Image) -> Image:
         result_img: Image = RGBImage(image_instance.getImageName())
         result_img.setImage(result)
 
+        # Extract and add QR/barcode metadata from filename (if present)
+        self._add_qr_metadata(result_img, image_instance.getImageName())
+
         # saves the calculated score to the image_instance as a parameter
         rating = FloatValue(
             "rating", "rating", "Granny calculated rating of total blush area."

Granny/Analyses/PeelColor.py

@@ -27,6 +27,7 @@
 from Granny.Models.Values.ImageListValue import ImageListValue
 from Granny.Models.Values.IntValue import IntValue
 from Granny.Models.Values.MetaDataValue import MetaDataValue
+from Granny.Models.Values.StringValue import StringValue
 from numpy.typing import NDArray
 
 
@@ -493,6 +494,9 @@ def _processImage(self, image_instance: Image) -> Image:
         )
         b_value.setValue(b)
 
+        # Extract and add QR/barcode metadata from filename (if present)
+        self._add_qr_metadata(image_instance, image_instance.getImageName())
+
         # adds ratings to  to the image_instance as parameters
         image_instance.addValue(
             bin_value,

Granny/Analyses/Segmentation.py

@@ -35,6 +35,7 @@
 from Granny.Models.Values.FloatValue import FloatValue
 from Granny.Models.Values.ImageListValue import ImageListValue
 from Granny.Models.Values.IntValue import IntValue
+from Granny.Utils.QRCodeDetector import QRCodeDetector
 from numpy.typing import NDArray
 
 
@@ -267,6 +268,10 @@ def __init__(self):
             )
         )
 
+        # Initialize QR code detector for variety information extraction
+        self.qr_detector = QRCodeDetector()
+        self.variety_info = None  # Will store detected variety information if QR code found
+
         self.addInParam(
             self.model,
             self.input_images,
@@ -542,7 +547,19 @@ def _extractImage(self, tray_image: Image) -> List[Image]:
             mask = sorted_masks[i]
             for channel in range(3):
                 individual_image[:, :, channel] = tray_image_array[y1:y2, x1:x2, channel] * mask[y1:y2, x1:x2]  # type: ignore
-            image_name = pathlib.Path(tray_image.getImageName()).stem + f"_fruit_{i+1:02d}" + ".png"
+
+            # Build filename: use QR data if detected, otherwise use default tray name
+            if self.variety_info is not None:
+                # QR code detected - use PROJECT_LOT_DATE_VARIETY_fruit_##.png
+                project = self.variety_info['project']
+                lot = self.variety_info['lot']
+                date = self.variety_info['date']
+                variety = self.variety_info['full']
+                image_name = f"{project}_{lot}_{date}_{variety}_fruit_{i+1:02d}.png"
+            else:
+                # No QR code - use default naming: tray_name_fruit_##.png
+                image_name = pathlib.Path(tray_image.getImageName()).stem + f"_fruit_{i+1:02d}" + ".png"
+
             image_instance: Image = RGBImage(image_name)
             image_instance.setImage(individual_image)
             individual_images.append(image_instance)
@@ -610,6 +627,22 @@ def performAnalysis(self) -> List[Image]:
             if h > w:
                 image_instance.rotateImage()
 
+            # Detect QR code to extract variety information (optional)
+            try:
+                qr_data, qr_points = self.qr_detector.detect(image_instance.getImage())
+                if qr_data:
+                    self.variety_info = self.qr_detector.extract_variety_info(qr_data)
+                    print(f"QR Code detected: {qr_data}")
+                    print(f"  Project: {self.variety_info['project']}, Lot: {self.variety_info['lot']}")
+                    print(f"  Date: {self.variety_info['date']}, Variety: {self.variety_info['full']}")
+                else:
+                    print("No QR code detected - using default naming")
+                    self.variety_info = None
+            except Exception as e:
+                # QR detection failed, continue with default naming
+                print(f"QR detection error: {str(e)} - using default naming")
+                self.variety_info = None
+
             # predicts fruit instances in the image
             result = self._segmentInstances(image=image_instance.getImage())
 
@@ -636,6 +669,7 @@ def performAnalysis(self) -> List[Image]:
 
                 self.masked_images.setImageList([masked_image])
                 self.masked_images.writeValue()
+
             except:
                 AttributeError("Error with the results.")
 

Granny/Analyses/StarchArea.py

@@ -28,6 +28,7 @@
 from Granny.Models.Values.ImageListValue import ImageListValue
 from Granny.Models.Values.IntValue import IntValue
 from Granny.Models.Values.MetaDataValue import MetaDataValue
+from Granny.Models.Values.StringValue import StringValue
 from numpy.typing import NDArray
 
 
@@ -420,6 +421,9 @@ def _processImage(self, image_instance: Image) -> Image:
         result_img: Image = RGBImage(image_instance.getImageName())
         result_img.setImage(result)
 
+        # Extract and add QR/barcode metadata from filename (if present)
+        self._add_qr_metadata(result_img, image_instance.getImageName())
+
         # saves the calculated score to the image_instance as a parameter
         rating = FloatValue(
             "rating", "rating", "Granny calculated rating of total starch area."

Granny/Analyses/SuperficialScald.py

@@ -28,6 +28,7 @@
 from Granny.Models.Values.ImageListValue import ImageListValue
 from Granny.Models.Values.IntValue import IntValue
 from Granny.Models.Values.MetaDataValue import MetaDataValue
+from Granny.Models.Values.StringValue import StringValue
 from numpy.typing import NDArray
 
 
@@ -367,6 +368,9 @@ def _processImage(self, image_instance: Image) -> Image:
         result_img: Image = RGBImage(image_instance.getImageName())
         result_img.setImage(binarized_image)
 
+        # Extract and add QR/barcode metadata from filename (if present)
+        self._add_qr_metadata(result_img, image_instance.getImageName())
+
         # saves the calculated score to the image_instance as a parameter
         rating = FloatValue(
             "rating", "rating", "Granny calculated rating of total starch area."

Granny/Models/Values/MetaDataValue.py

@@ -47,7 +47,13 @@ def writeValue(self):
         )
         image_rating.to_csv(os.path.join(self.value, "results.csv"), header=True, index=False)
         tray_avg = image_rating.drop(columns=["Name"])
-        tray_avg = tray_avg.groupby("TrayName").mean().reset_index()
+        string_cols = tray_avg.select_dtypes(include=["object"]).columns.difference(["TrayName"]).tolist()
+        tray_numeric = tray_avg.groupby("TrayName").mean(numeric_only=True).reset_index()
+        if string_cols:
+            tray_strings = tray_avg.groupby("TrayName")[string_cols].first().reset_index()
+            tray_avg = tray_strings.merge(tray_numeric, on="TrayName")
+        else:
+            tray_avg = tray_numeric
         tray_avg.to_csv(os.path.join(self.value, "tray_summary.csv"), header=True, index=False)
 
     def getImageList(self):