Update app.py

app.py

@@ -22,7 +22,7 @@ def classify_image_with_overlay(img):
     img_pil = Image.fromarray(img)
 
     # Predict the label and probability
-    label, probability = classifier.predict_image(img=img_pil)
+    prediction = classifier.predict_image(img=img_pil)
 
     # Load the image using OpenCV
     image = cv2.cvtColor(np.array(img_pil), cv2.COLOR_RGB2BGR)
@@ -33,17 +33,22 @@ def classify_image_with_overlay(img):
     font_scale = 1.5  # Increase the font size
     color = (255, 255, 255)  # White color
     thickness = 2
-    text_size = cv2.getTextSize(f"{label}: {probability:.2f}", font, font_scale, thickness)[0]
+    text = f"{prediction['label']}: {prediction['probability']:.2f}"
+
+    text_size = cv2.getTextSize(text, font, font_scale, thickness)[0]
     cv2.rectangle(image, (org[0] - 10, org[1] - text_size[1] - 10), (org[0] + text_size[0], org[1]), color, cv2.FILLED)
 
     # Put the label text on the white rectangle
-    cv2.putText(image, f"{label}: {probability:.2f}", org, font, font_scale, (0, 0, 0), thickness, cv2.LINE_AA)
+    cv2.putText(image, text, org, font, font_scale, (0, 0, 0), thickness, cv2.LINE_AA)
 
     # Resize the image to a larger size
     image = cv2.resize(image, (800, 800))  # Defina o tamanho desejado aqui
 
     return image
 
+# ...
+
+
 iface = gr.Interface(
     fn=classify_image_with_overlay,
     inputs=gr.inputs.Image(),