Update app.py

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 import cv2
 import numpy as np
-import matplotlib.pyplot as plt
 import json
 import math
 
@@ -69,14 +68,14 @@ def detect_and_match(img1_gray, img2_gray, detector_name, ratio_thresh=0.78):
 # === Main processing ===
 def process_images(flat_img, persp_img, json_file):
     if flat_img is None or persp_img is None or json_file is None:
-        return [None]*6
+        return []
 
     # Load JSON
     try:
         data = json.load(open(json_file.name))
     except Exception as e:
         print("JSON read error:", e)
-        return [None]*6
+        return []
 
     roi = data["printAreas"][0]
     roi_x = roi["position"]["x"]
@@ -90,13 +89,12 @@ def process_images(flat_img, persp_img, json_file):
     persp_gray = preprocess_gray_clahe(persp_img)
 
     detectors = ["SIFT", "ORB", "BRISK", "AKAZE", "KAZE"]
-    results = []
+    gallery_images = []
 
     for det in detectors:
         kp1, kp2, good_matches = detect_and_match(flat_gray, persp_gray, det)
         if len(good_matches) < 4:
             print(f"Not enough matches for {det}")
-            results.append(None)
             continue
 
         src_pts = np.float32([kp1[m.queryIdx].pt for m in good_matches]).reshape(-1,1,2)
@@ -107,38 +105,30 @@ def process_images(flat_img, persp_img, json_file):
         roi_corners_flat = get_rotated_rect_corners(roi_x, roi_y, roi_w, roi_h, roi_rot_deg)
         roi_corners_persp = cv2.perspectiveTransform(roi_corners_flat.reshape(-1,1,2), H).reshape(-1,2)
 
-        # Draw ROI
-        flat_out = flat_img.copy()
+        # Draw ROI on Perspective image only
         persp_out = persp_img.copy()
-        cv2.polylines(flat_out, [roi_corners_flat.astype(int)], True, (255,0,0), 3)
         cv2.polylines(persp_out, [roi_corners_persp.astype(int)], True, (0,255,0), 3)
 
-        results.append([flat_out, persp_out])
+        # Add detector label
+        cv2.putText(persp_out, f"{det}", (10,30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,255), 2)
 
-    return results  # List of [flat_out, persp_out] for each detector
+        gallery_images.append(persp_out)
 
-# === Gradio Interface ===
-def wrap_gradio(flat_img, persp_img, json_file):
-    outputs = process_images(flat_img, persp_img, json_file)
-    # Flatten the outputs for Gallery display
-    gallery_images = []
-    for item in outputs:
-        if item is not None:
-            gallery_images.extend([item[0], item[1]])
     return gallery_images
 
+# === Gradio Interface ===
 iface = gr.Interface(
-    fn=wrap_gradio,
+    fn=process_images,
     inputs=[
         gr.Image(type="numpy", label="Flat Image"),
         gr.Image(type="numpy", label="Perspective Image"),
         gr.File(type="filepath", label="JSON File")
     ],
     outputs=[
-        gr.Gallery(label="Results (Flat + Perspective per Detector)")
+        gr.Gallery(label="Detector-wise Perspective ROI Projection", show_label=True)
     ],
     title="Feature Detection with ROI Projection",
-    description="Shows SIFT, ORB, BRISK, AKAZE, KAZE feature-based ROI projections. Each detector outputs Flat and Perspective images."
+    description="Shows SIFT, ORB, BRISK, AKAZE, KAZE feature-based ROI projections on the Perspective image only."
 )
 
 iface.launch()