Update app.py

app.py

@@ -10,6 +10,8 @@ import numpy as np
 from PIL import Image
 import torch
 from huggingface_hub import HfApi
+
+# Adjust import paths as needed
 sys.path.append('Utils')
 sys.path.append('model')
 from model.CBAM.reunet_cbam import reunet_cbam
@@ -19,8 +21,21 @@ from Utils.area import pixel_to_sqft, process_and_overlay_image
 from split_merge import split, merge 
 from Utils.convert import read_pansharpened_rgb
 
+# Initialize Hugging Face API
+hf_api = HfApi()
+
+# Get the token from secrets
+HF_TOKEN = st.secrets.get("HF_TOKEN")
+if not HF_TOKEN:
+    st.error("HF_TOKEN not found in secrets. Please set it in your Space's Configuration > Secrets.")
+    st.stop()
+
+# Your Space ID (this should match exactly with your Hugging Face Space URL)
+REPO_ID = "Pavan2k4/Building_area"
+REPO_TYPE = "space"
+
 # Define base directory for Hugging Face Spaces
-BASE_DIR = "data"
+BASE_DIR = "data/"
 
 # Define subdirectories
 UPLOAD_DIR = os.path.join(BASE_DIR, "uploaded_images")
@@ -33,18 +48,6 @@ CSV_LOG_PATH = os.path.join(BASE_DIR, "image_log.csv")
 for directory in [UPLOAD_DIR, MASK_DIR, PATCHES_DIR, PRED_PATCHES_DIR]:
     os.makedirs(directory, exist_ok=True)
 
-# Initialize Hugging Face API
-hf_api = HfApi()
-
-# Get the token from environment variable
-HF_TOKEN = os.environ.get("HF_TOKEN")
-if not HF_TOKEN:
-    st.error("HF_TOKEN not found in environment variables. Please set it in your Space settings.")
-    st.stop()
-
-
-REPO_ID = "Pavan2k4/Building_area" 
-
 # Load model
 @st.cache_resource
 def load_model():
@@ -66,11 +69,14 @@ def save_to_hf_repo(local_path, repo_path):
             path_or_fileobj=local_path,
             path_in_repo=repo_path,
             repo_id=REPO_ID,
+            repo_type=REPO_TYPE,
             token=HF_TOKEN
         )
         st.success(f"File uploaded successfully to {repo_path}")
     except Exception as e:
         st.error(f"Error uploading file: {str(e)}")
+        st.error("Detailed error information:")
+        st.exception(e)
 
 def log_image_details(image_id, image_filename, mask_filename):
     file_exists = os.path.exists(CSV_LOG_PATH)
@@ -258,7 +264,7 @@ def result_page():
         original_np = cv2.imread(original_img_path)
         mask_np = cv2.imread(mask_path, cv2.IMREAD_GRAYSCALE)
         
-        #  mask is binary
+        # Ensure mask is binary
         _, mask_np = cv2.threshold(mask_np, 127, 255, cv2.THRESH_BINARY)
 
         # Resize mask to match original image size if necessary