Update app.py

app.py

@@ -2,9 +2,8 @@ import cv2
 import numpy as np
 import json
 import gradio as gr
-import matplotlib.pyplot as plt
 
-# === Helper: Rotated rectangle corners ===
+# Helper functions remain same
 def get_rotated_rect_corners(x, y, w, h, rotation_deg):
     rot_rad = np.deg2rad(rotation_deg)
     cos_r = np.cos(rot_rad)
@@ -27,13 +26,11 @@ def get_rotated_rect_corners(x, y, w, h, rotation_deg):
     corners = rotated_corners + np.array([cx, cy])
     return corners.astype(np.float32)
 
-# === Preprocessing: Grayscale + CLAHE ===
 def preprocess_gray_clahe(img):
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8))
     return clahe.apply(gray)
 
-# === Detect and match features ===
 def detect_and_match(img1_gray, img2_gray, method="SIFT", ratio_thresh=0.78):
     if method == "SIFT":
         sift = cv2.SIFT_create(nfeatures=5000)
@@ -70,11 +67,11 @@ def detect_and_match(img1_gray, img2_gray, method="SIFT", ratio_thresh=0.78):
             good.append(m)
     return kp1, kp2, good
 
-# === Main function for Gradio ===
+# Main function
 def homography_demo(flat_file, persp_file, json_file):
-    flat_img = cv2.imdecode(np.frombuffer(flat_file.read(), np.uint8), cv2.IMREAD_COLOR)
-    persp_img = cv2.imdecode(np.frombuffer(persp_file.read(), np.uint8), cv2.IMREAD_COLOR)
-    mockup = json.load(json_file)
+    flat_img = cv2.imread(flat_file.name)
+    persp_img = cv2.imread(persp_file.name)
+    mockup = json.load(open(json_file.name))
 
     roi_data = mockup["printAreas"][0]["position"]
     roi_x = roi_data["x"]
@@ -91,38 +88,31 @@ def homography_demo(flat_file, persp_file, json_file):
 
     for method in methods:
         kp1, kp2, good_matches = detect_and_match(flat_gray, persp_gray, method=method)
-
-        src_pts = np.float32([kp1[m.queryIdx].pt for m in good_matches]).reshape(-1, 1, 2)
-        dst_pts = np.float32([kp2[m.trainIdx].pt for m in good_matches]).reshape(-1, 1, 2)
-
+        src_pts = np.float32([kp1[m.queryIdx].pt for m in good_matches]).reshape(-1,1,2)
+        dst_pts = np.float32([kp2[m.trainIdx].pt for m in good_matches]).reshape(-1,1,2)
         H, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
 
         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)
+        roi_corners_persp = cv2.perspectiveTransform(roi_corners_flat.reshape(-1,1,2), H).reshape(-1,2)
 
         persp_debug = persp_img.copy()
-        cv2.polylines(persp_debug, [roi_corners_persp.astype(int)], True, (0, 255, 0), 2)
+        cv2.polylines(persp_debug, [roi_corners_persp.astype(int)], True, (0,255,0), 2)
         for (px, py) in roi_corners_persp:
-            cv2.circle(persp_debug, (int(px), int(py)), 5, (255, 0, 0), -1)
+            cv2.circle(persp_debug, (int(px), int(py)), 5, (255,0,0), -1)
 
-        # Convert BGR to RGB for Gradio display
-        persp_debug_rgb = cv2.cvtColor(persp_debug, cv2.COLOR_BGR2RGB)
-        outputs.append((persp_debug_rgb, method))
+        outputs.append(cv2.cvtColor(persp_debug, cv2.COLOR_BGR2RGB))
 
     return outputs
 
-# === Gradio Interface ===
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## Homography ROI Demo with Multiple Feature Detectors")
     with gr.Row():
-        flat_input = gr.File(label="Upload Flat Image")
-        persp_input = gr.File(label="Upload Perspective Image")
-        json_input = gr.File(label="Upload mockup.json")
-    output_gallery = gr.Gallery(label="Perspective ROI Results", show_label=True, elem_id="gallery", columns=2, height=400)
+        flat_input = gr.File(label="Upload Flat Image", file_types=[".jpg",".png",".jpeg"])
+        persp_input = gr.File(label="Upload Perspective Image", file_types=[".jpg",".png",".jpeg"])
+        json_input = gr.File(label="Upload mockup.json", file_types=[".json"])
+    output_gallery = gr.Gallery(label="Perspective ROI Results", columns=2, height=400)
     run_btn = gr.Button("Run Homography")
-
-    run_btn.click(homography_demo, 
-                  inputs=[flat_input, persp_input, json_input],
-                  outputs=output_gallery)
+    run_btn.click(homography_demo, inputs=[flat_input, persp_input, json_input], outputs=output_gallery)
 
 demo.launch()