add logging and examples

app.py

@@ -1,3 +1,4 @@
+import logging
 import math
 
 import cv2
@@ -6,6 +7,8 @@ import numpy as np
 import onnxruntime as ort
 from PIL import Image, ImageOps
 
+logging.basicConfig(format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+
 MODEL_PATH = "model.onnx"
 IMAGE_SIZE = 480
 
@@ -68,7 +71,7 @@ def rectify(img_np: np.ndarray, keypoints: np.ndarray):
         w = h * wh_ratio
 
     except:
-        print("Failed to estimate aspect ratio from perspective")
+        logging.exception("Failed to estimate aspect ratio from perspective")
         w1 = distance(keypoints[0], keypoints[1])
         w2 = distance(keypoints[3], keypoints[2])
         w = (w1 + w2) * 0.5
@@ -86,7 +89,14 @@ def predict(img: Image.Image):
     kpts_xy = pred_kpts[:, :2] * max(img.size) / IMAGE_SIZE
 
     img_np = np.array(img)
-    cv2.polylines(img_np, [kpts_xy.astype(int)], True, (0, 255, 0), thickness=5, lineType=cv2.LINE_AA)
+    cv2.polylines(
+        img_np,
+        [kpts_xy.astype(int)],
+        True,
+        (0, 255, 0),
+        thickness=5,
+        lineType=cv2.LINE_AA,
+    )
 
     if (pred_kpts[:, 2] >= 0.25).all():
         cropped = rectify(np.array(img), kpts_xy)
@@ -100,4 +110,5 @@ gr.Interface(
     predict,
     inputs=[gr.Image(type="pil")],
     outputs=["image", "image"],
+    examples=["estonia_id_card.jpg", "german_bundesdruckerei_passport.webp"],
 ).launch(server_name="0.0.0.0")