Update app.py

app.py

@@ -17,6 +17,7 @@ import gc
 from scalingtestupdated import calculate_scaling_factor
 from scipy.interpolate import splprep, splev
 from scipy.ndimage import gaussian_filter1d
+import json
 
 
 birefnet = AutoModelForImageSegmentation.from_pretrained(
@@ -267,11 +268,23 @@ def detect_reference_square(img) -> np.ndarray:
 def resize_img(img: np.ndarray, resize_dim):
     return np.array(Image.fromarray(img).resize(resize_dim))
 
-def predict(image, offset_inches):
+
+# Load selected language file
+def load_language(lang_code):
+    with open(f'./locales/{lang_code}.json', 'r') as f:
+        return json.load(f)
+
+def predict(image, offset, language):
+    # Load the selected language
+    translations = load_language(language)
+
+    if offset <= -1:
+        raise gr.Error(translations["offset_error"])
+
     try:
         reference_obj_img, scaling_box_coords = detect_reference_square(image)
-    except Exception as e:
-        raise gr.Error(f"Unable to DETECT COIN, please take another picture with different magnification level! Error: {e}")
+    except:
+        raise gr.Error(translations["offset_error"])
 
     reference_obj_img = make_square(reference_obj_img)
     reference_square_mask = remove_bg(reference_obj_img)
@@ -310,7 +323,7 @@ def predict(image, offset_inches):
     
     # Ensure offset_inches is valid
     if scaling_factor != 0:
-        offset_pixels = (offset_inches / scaling_factor) * 2 + 1
+        offset_pixels = (offset / scaling_factor) * 2 + 1
     else:
         offset_pixels = 1  # Default value in case of invalid scaling factor
 
@@ -329,30 +342,64 @@ def predict(image, offset_inches):
         scaling_factor,
     )
 
-if __name__ == "__main__":
+if __name__ == "__main__": 
     os.makedirs("./outputs", exist_ok=True)
 
+    # Language selector in UI
     ifer = gr.Interface(
         fn=predict,
         inputs=[
-            gr.Image(label="Input Image"),
-            gr.Number(label="Offset value for Mask(inches)", value=0.075),
+            gr.Image(label="Input Image", type="numpy"),
+            gr.Number(label="Offset value for Mask(mm)", value=2),
+            gr.Dropdown(["en", "nl"], label="Language", value="en")  # Default English
         ],
         outputs=[
-            gr.Image(label="Ouput Image"),
+            gr.Image(label="Output 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 inches",
+                placeholder="Every pixel is equal to mentioned number in millimeters",
             ),
         ],
         examples=[
-            ["./examples/Test20.jpg", 0.075],
-            ["./examples/Test21.jpg", 0.075],
-            ["./examples/Test22.jpg", 0.075],
-            ["./examples/Test23.jpg", 0.075],
+            ["./examples/Test20.jpg", 2, "en"],
+            ["./examples/Test21.jpg", 2, "en"],
+            ["./examples/Test22.jpg", 2, "nl"],
+            ["./examples/Test23.jpg", 2, "nl"],
         ],
     )
-    ifer.launch(share=True)
+    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)
+
+
+