Update app.py

app.py

@@ -1,38 +1,62 @@
 import gradio as gr
 import cv2
 import numpy as np
+import json
 
-def detect_aruco_markers(image):
+def detect_aruco_markers(image, dictionary_preset,
+                         cornerRefinementMethod, detectInvertedMarker, adaptiveThreshConstant):
     # Convert to grayscale
     gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
-    
+
     # Load predefined dictionary
-    aruco_dict = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_6X6_250)
-    
+    aruco_dict = cv2.aruco.getPredefinedDictionary(getattr(cv2.aruco, dictionary_preset))
+
     # Initialize detector parameters
     parameters = cv2.aruco.DetectorParameters()
+    parameters.cornerRefinementMethod = getattr(cv2.aruco, cornerRefinementMethod)
+    parameters.detectInvertedMarker = detectInvertedMarker
+    parameters.adaptiveThreshConstant = adaptiveThreshConstant
+
     detector = cv2.aruco.ArucoDetector(aruco_dict, parameters)
+
     # Detect markers
     corners, ids, rejected = detector.detectMarkers(gray)
-    #print ids
-    print(ids)
+    print("Detected IDs:", ids)
 
-    
-    # Draw detected markers
+    detections = []
     if ids is not None:
         annotated_image = cv2.aruco.drawDetectedMarkers(image.copy(), corners, ids)
+        for i in range(len(ids)):
+            marker_info = {
+                "id": int(ids[i][0]),
+                "corners": [np.array(corner).tolist() for corner in corners[i]]
+            }
+            detections.append(marker_info)
     else:
         annotated_image = image.copy()
-    
-    return annotated_image
+
+    return annotated_image, json.dumps(detections, indent=4)
+
+# Available ArUco dictionary presets
+dictionary_choices = [name for name in dir(cv2.aruco) if name.startswith("DICT_")]
+corner_refinement_choices = ["CORNER_REFINE_NONE", "CORNER_REFINE_SUBPIX", "CORNER_REFINE_CONTOUR", "CORNER_REFINE_APRILTAG"]
 
 # Gradio interface
 iface = gr.Interface(
     fn=detect_aruco_markers,
-    inputs=gr.Image(type="numpy"),
-    outputs=gr.Image(type="numpy"),
-    title="ArUco Marker Detector",
-    description="Upload an image and detect ArUco markers using OpenCV."
+    inputs=[
+        gr.Image(type="numpy"),
+        gr.Dropdown(choices=dictionary_choices, label="Dictionary Preset", value="DICT_6X6_250"),	
+        gr.Dropdown(choices=corner_refinement_choices, label="Corner Refinement Method", value="CORNER_REFINE_NONE"),
+        gr.Checkbox(label="Detect Inverted Marker", value=False),
+        gr.Slider(minimum=3, maximum=201, step=2, label="Adaptive Thresh", value=7),
+    ],
+    outputs=[
+        gr.Image(type="numpy", label="Detected Markers"),
+        gr.Code(label="Detection Data (JSON)", language="json")
+    ],
+    title="ArUco Marker Detector with Parameter Control",
+    description="Upload an image and adjust ArUco detection parameters. The detected markers are drawn on the image, and the detection data (IDs and corner coordinates) is provided in JSON format.",
 )
 
 if __name__ == "__main__":