Update app.py

app.py

@@ -3,7 +3,7 @@ import numpy as np
 import json
 import gradio as gr
 
-# Helper functions remain same
+# ---------------- Your Original Functions (Unchanged) ---------------- #
 def get_rotated_rect_corners(x, y, w, h, rotation_deg):
     rot_rad = np.deg2rad(rotation_deg)
     cos_r = np.cos(rot_rad)
@@ -67,11 +67,16 @@ def detect_and_match(img1_gray, img2_gray, method="SIFT", ratio_thresh=0.78):
             good.append(m)
     return kp1, kp2, good
 
-# Main function
-def homography_demo(flat_file, persp_file, json_file):
-    flat_img = cv2.imread(flat_file.name)
-    persp_img = cv2.imread(persp_file.name)
-    mockup = json.load(open(json_file.name))
+# ---------------- Processing Function for Gradio ---------------- #
+def homography_all_detectors(flat_img, persp_img, json_file):
+    if flat_img is None or persp_img is None:
+        return [None] * 6
+    
+    flat_bgr = cv2.cvtColor(flat_img, cv2.COLOR_RGB2BGR)
+    persp_bgr = cv2.cvtColor(persp_img, cv2.COLOR_RGB2BGR)
+
+    with open(json_file.name, 'r') as f:
+        mockup = json.load(f)
 
     roi_data = mockup["printAreas"][0]["position"]
     roi_x = roi_data["x"]
@@ -80,13 +85,14 @@ def homography_demo(flat_file, persp_file, json_file):
     roi_h = mockup["printAreas"][0]["height"]
     roi_rot_deg = mockup["printAreas"][0]["rotation"]
 
-    flat_gray = preprocess_gray_clahe(flat_img)
-    persp_gray = preprocess_gray_clahe(persp_img)
+    flat_gray = preprocess_gray_clahe(flat_bgr)
+    persp_gray = preprocess_gray_clahe(persp_bgr)
 
-    methods = ["SIFT", "ORB", "BRISK", "KAZE", "AKAZE"]
-    outputs = []
+    detectors = ["SIFT", "ORB", "BRISK", "KAZE", "AKAZE"]
+    gallery_images = []
+    download_files = [None] * 5
 
-    for method in methods:
+    for i, method in enumerate(detectors):
         kp1, kp2, good_matches = detect_and_match(flat_gray, persp_gray, method=method)
         if kp1 is None or kp2 is None or len(good_matches) < 4:
             continue
@@ -101,32 +107,38 @@ def homography_demo(flat_file, persp_file, 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)
 
-        persp_debug = persp_img.copy()
+        persp_debug = persp_bgr.copy()
         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)
 
-        outputs.append((f"{method} Result", cv2.cvtColor(persp_debug, cv2.COLOR_BGR2RGB)))
-
-    return outputs
-
-# 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", 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"])
-    with gr.Row():
-        flat_preview = gr.Image(type="filepath", label="Flat Image Preview", height=200)
-        persp_preview = gr.Image(type="filepath", label="Perspective Image Preview", height=200)
-    output_gallery = gr.Gallery(label="Perspective ROI Results", show_label=True, columns=2, height=600)
-    run_btn = gr.Button("Run Homography")
-
-    # Link previews
-    flat_input.change(lambda f: f.name if f else None, inputs=flat_input, outputs=flat_preview)
-    persp_input.change(lambda f: f.name if f else None, inputs=persp_input, outputs=persp_preview)
-
-    run_btn.click(homography_demo, inputs=[flat_input, persp_input, json_input], outputs=output_gallery)
-
-demo.launch()
+        result_rgb = cv2.cvtColor(persp_debug, cv2.COLOR_BGR2RGB)
+        file_name = f"result_{method.lower()}.png"
+        cv2.imwrite(file_name, result_rgb[:, :, ::-1])  # save as BGR
+
+        gallery_images.append((f"{method} Result", result_rgb))
+        download_files[i] = file_name
+
+    return [gallery_images] + download_files
+
+# ---------------- Gradio Interface ---------------- #
+iface = gr.Interface(
+    fn=homography_all_detectors,
+    inputs=[
+        gr.Image(type="numpy", label="Image 1 (Flat)"),
+        gr.Image(type="numpy", label="Image 2 (Perspective)"),
+        gr.File(type="filepath", label="JSON File")
+    ],
+    outputs=[
+        gr.Gallery(label="Results"),
+        gr.File(label="Download SIFT Result"),
+        gr.File(label="Download ORB Result"),
+        gr.File(label="Download BRISK Result"),
+        gr.File(label="Download KAZE Result"),
+        gr.File(label="Download AKAZE Result")
+    ],
+    title="Homography ROI Projection with Multiple Feature Detectors",
+    description="Upload a flat image, a perspective image, and the JSON file. The system will compute homography with SIFT, ORB, BRISK, KAZE, and AKAZE, project the bounding box, and allow result download."
+)
+
+iface.launch()