Update app.py

app.py

@@ -297,7 +297,6 @@ def predict(image, offset, coin_size_mm):
 
     try:
         scaling_factor= calculate_scaling_factor(
-            reference_image_path="./coin.jpg",
             target_image=reference_square_mask,
             reference_obj_size_mm = coin_size_mm,
             feature_detector="ORB",
@@ -356,7 +355,7 @@ if __name__ == "__main__":
             gr.Image(label="Input Image", type="numpy"),
             gr.Number(label="Offset value for Mask(mm)", value=0.15),
             gr.Number(label="Diameter of reference coin(mm). Adjust according to coin.", value=20),
-            # gr.Dropdown(["en", "nl"], label="Language", value="en")  # Default English
+        
         ],
         outputs=[
             gr.Image(label="Output Image"),
@@ -378,33 +377,5 @@ if __name__ == "__main__":
     ifer.launch(share=True)
 
 
-# if __name__ == "__main__":
-#     os.makedirs("./outputs", exist_ok=True)
-
-#     ifer = gr.Interface(
-#         fn=predict,
-#         inputs=[
-#             gr.Image(label="Input Image"),
-#             gr.Number(label="Offset value for Mask(mm)", value=2),
-#         ],
-#         outputs=[
-#             gr.Image(label="Ouput Image"),
-#             gr.Image(label="Outlines of Objects"),
-#             gr.File(label="DXF file"),
-#             gr.Image(label="Mask"),
-#             gr.Textbox(
-#                 label="Scaling Factor(mm)",
-#                 placeholder="Every pixel is equal to mentioned number in millimeters",
-#             ),
-#         ],
-#         examples=[
-#             ["./examples/Test20.jpg", 2],
-#             ["./examples/Test21.jpg", 2],
-#             ["./examples/Test22.jpg", 2],
-#             ["./examples/Test23.jpg", 2],
-#         ],
-#     )
-#     ifer.launch(share=True)
-