Update to use ONNX

app.py

@@ -50,8 +50,12 @@ class Model:
 
 def draw_boxes(image: Image.Image, outputs: dict):
     draw = ImageDraw.Draw(image)
+
+    # Dynamic font size based on image width
+    image_width, image_height = image.size
+    font_size = max(15, image_width // 100)  # Adjust as needed
     try:
-        font = ImageFont.truetype("arial.ttf", size=16)
+        font = ImageFont.truetype("arial.ttf", size=font_size)
     except IOError:
         font = ImageFont.load_default()
 
@@ -63,18 +67,31 @@ def draw_boxes(image: Image.Image, outputs: dict):
         if score < PROB_THRESHOLD:
             continue
         label = LABELS[int(cls)]
+
         # Assuming box format: [ymin, xmin, ymax, xmax] normalized [0,1]
         ymin, xmin, ymax, xmax = box
-        width, height = image.size
-        left = xmin * width
-        right = xmax * width
-        top = ymin * height
-        bottom = ymax * height
+        left = xmin * image_width
+        right = xmax * image_width
+        top = ymin * image_height
+        bottom = ymax * image_height
+
+        # Draw bounding box
         draw.rectangle([left, top, right, bottom], outline="red", width=2)
+
+        # Prepare label text
         text = f"{label}: {score:.2f}"
-        text_size = draw.textsize(text, font=font)
-        draw.rectangle([left, top - text_size[1], left + text_size[0], top], fill="red")
-        draw.text((left, top - text_size[1]), text, fill="white", font=font)
+
+        # Calculate text size using textbbox
+        text_bbox = draw.textbbox((0, 0), text, font=font)
+        text_width = text_bbox[2] - text_bbox[0]
+        text_height = text_bbox[3] - text_bbox[1]
+
+        # Draw rectangle behind text for better visibility
+        draw.rectangle([left, top - text_height - 4, left + text_width + 4, top], fill="red")
+
+        # Draw text
+        draw.text((left + 2, top - text_height - 2), text, fill="white", font=font)
+
     return image
 
 # Initialize model
@@ -107,9 +124,9 @@ iface = gr.Interface(
     outputs=[gr.Image(type="pil", label="Detected Objects"), gr.Textbox(label="Detections")],
     title="Object Detection with ONNX Model",
     description="Upload an image to detect objects using the ONNX model.",
-    examples=["examples/card1.jpg", "examples/card2.jpg", "examples/card3.jpg"]
+    examples=["examples/card1.jpg", "examples/card2.jpg", "examples/card3.jpg"],
+    theme="default"  # You can choose other themes if desired
 )
 
 if __name__ == "__main__":
     iface.launch()
-

requirements.txt

@@ -1,5 +1,5 @@
 gradio==3.32.0
 onnx==1.14.0
 onnxruntime==1.15.1
-Pillow==9.5.0
+Pillow>=10.0.0
 numpy==1.25.0