Fix Gradio compatibility: upgrade to v6.5+ and simplify type annotations

.gitignore

@@ -0,0 +1,3 @@
+.venv/
+__pycache__/
+*.pyc

app.py

@@ -31,7 +31,7 @@ def setup_yolo():
         return False
 
 
-def predict_yolo(image: Image.Image) -> tuple[Corners | None, str]:
+def predict_yolo(image):
     if not setup_yolo():
         return None, "YOLO model not available"
 
@@ -64,7 +64,7 @@ def predict_yolo(image: Image.Image) -> tuple[Corners | None, str]:
         os.unlink(temp_path)
 
 
-def process_single_image(image: Image.Image) -> tuple[Image.Image | None, str]:
+def process_single_image(image):
     yolo_corners, yolo_status = predict_yolo(image)
 
     yolo_viz = None
@@ -78,7 +78,7 @@ def process_single_image(image: Image.Image) -> tuple[Image.Image | None, str]:
     return yolo_viz, yolo_info
 
 
-def process_images(images: list) -> list[dict]:
+def process_images(images):
     results = []
 
     if images is None:
@@ -92,7 +92,6 @@ def process_images(images: list) -> list[dict]:
             image = img_data
             filename = "uploaded_image"
         else:
-            # Handle other cases if necessary, e.g. file objects
             try:
                 image = Image.open(img_data)
                 filename = "uploaded_image"
@@ -111,7 +110,7 @@ def process_images(images: list) -> list[dict]:
     return results
 
 
-def create_gallery_output(results: list[dict]) -> tuple:
+def create_gallery_output(results):
     yolo_images = []
 
     for r in results:
@@ -125,7 +124,7 @@ def create_gallery_output(results: list[dict]) -> tuple:
     return yolo_images, yolo_info
 
 
-def predict(images: list[str] | None) -> tuple[list, str]:
+def predict(images):
     if images is None or len(images) == 0:
         return [], "No images uploaded"
 
@@ -151,8 +150,7 @@ with gr.Blocks(title="Squircle Corners Prediction") as demo:
             input_images = gr.File(
                 label="Upload Images",
                 file_count="multiple",
-                file_types=["image"],
-                type="filepath"
+                file_types=["image"]
             )
             predict_btn = gr.Button("Predict", variant="primary")
 

requirements.txt

@@ -1,4 +1,4 @@
-gradio>=4.44.0,<5.0.0
+gradio>=6.5.0
 numpy<2
 albumentations>=1.4.0
 Pillow>=10.0.0