Update app.py

app.py

@@ -9,7 +9,7 @@ import cv2
 import numpy as np
 from PIL import Image
 import torch
-from huggingface_hub import hf_hub_download
+
 
 sys.path.append('Utils')
 sys.path.append('model')
@@ -18,17 +18,7 @@ from model.transform import transforms
 from model.unet import UNET
 from Utils.area import pixel_to_sqft, process_and_overlay_image
 from Utils.convert import read_pansharpened_rgb
-from huggingface_hub import HfApi, login
-
-HF_TOKEN = os.environ.get("HF_TOKEN")
-if not HF_TOKEN:
-    raise ValueError("HF_TOKEN environment variable is not set")
-
-login(token=HF_TOKEN)
-hf_api = HfApi()
 
-REPO_ID = "Pavan2k4/Building_area"
-REPO_TYPE = "space"
 
 @st.cache_resource
 def load_model():
@@ -71,24 +61,7 @@ def refine_mask(mask, blur_kernel=5, threshold_value=127, morph_kernel_size=3, m
 
 
 # save to dir func
-def save_to_hf_repo(local_path, repo_path):
-    if not os.path.isfile(local_path):
-        st.error(f"File not found at {local_path}")
-        return
-    
-    try:
-        with open(local_path, 'rb') as f:
-            hf_api.upload_file(
-                path_or_fileobj=f,
-                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 during upload: {str(e)}")
-        st.exception(e)
+
 
 
 
@@ -202,13 +175,12 @@ def log_image_details(image_id, image_filename, mask_filename):
         
         writer.writerow([sno, date, time, image_id, image_filename, mask_filename])
 
+
 def upload_page():
     if 'file_uploaded' not in st.session_state:
         st.session_state.file_uploaded = False
-    
     if 'filename' not in st.session_state:
         st.session_state.filename = None
-    
     if 'mask_filename' not in st.session_state:
         st.session_state.mask_filename = None
 
@@ -217,7 +189,6 @@ def upload_page():
     if image is not None and not st.session_state.file_uploaded:
         try:
             bytes_data = image.getvalue()
-            
             timestamp = int(time.time())
             original_filename = image.name
             file_extension = os.path.splitext(original_filename)[1].lower()
@@ -235,7 +206,6 @@ def upload_page():
             with open(filepath, "wb") as f:
                 f.write(bytes_data)
             
-            # Check if the uploaded file is a GeoTIFF
             if file_extension in ['.tiff', '.tif']:
                 st.info('Processing GeoTIFF image...')
                 rgb_image = read_pansharpened_rgb(filepath)
@@ -256,13 +226,10 @@ def upload_page():
             st.image(img, caption='Uploaded Image', use_column_width=True)
             st.success(f'Image processed and saved as {converted_filename}')
 
-            # Store the full path of the converted image
             st.session_state.filename = converted_filename
 
-            # Convert image to numpy array
             img_array = np.array(img)
 
-            # Check if image shape is more than 650x650
             if img_array.shape[0] > 650 or img_array.shape[1] > 650:
                 st.info('Large image detected. Using patch-based processing.')
                 with st.spinner('Analyzing large image...'):
@@ -274,45 +241,12 @@ def upload_page():
                     prediction = predict(img_transformed)
                     full_mask = (prediction > 0.5).astype(np.uint8) * 255
 
-            # Save the full mask
             full_mask = refine_mask(full_mask)
             mask_filename = f"mask_{timestamp}.png"
             mask_filepath = os.path.join(MASK_DIR, mask_filename)
             cv2.imwrite(mask_filepath, full_mask)
             st.session_state.mask_filename = mask_filename
 
-            # Upload to Hugging Face repo
-            try:
-                with open(converted_filepath, 'rb') as f:
-                    image_repo_path = f"images/{converted_filename}"
-                    hf_api.upload_file(
-                        path_or_fileobj=f,
-                        path_in_repo=image_repo_path,
-                        repo_id=REPO_ID,
-                        repo_type=REPO_TYPE,
-                        token=HF_TOKEN
-                    )
-                st.success(f"Image uploaded successfully to {image_repo_path}")
-            except Exception as e:
-                st.error(f"Error saving image to Hugging Face repo: {str(e)}")
-                st.exception(e)
-
-            try:
-                with open(mask_filepath, 'rb') as f:
-                    mask_repo_path = f"masks/{mask_filename}"
-                    hf_api.upload_file(
-                        path_or_fileobj=f,
-                        path_in_repo=mask_repo_path,
-                        repo_id=REPO_ID,
-                        repo_type=REPO_TYPE,
-                        token=HF_TOKEN
-                    )
-                st.success(f"Mask uploaded successfully to {mask_repo_path}")
-            except Exception as e:
-                st.error(f"Error saving mask to Hugging Face repo: {str(e)}")
-                st.exception(e)
-
-            # Log image details
             log_image_details(timestamp, converted_filename, mask_filename)
 
             st.session_state.file_uploaded = True
@@ -321,7 +255,7 @@ def upload_page():
         except Exception as e:
             st.error(f"An error occurred: {str(e)}")
             st.error("Please check the logs for more details.")
-            print(f"Error in upload_page: {str(e)}")  # This will appear in the Streamlit logs
+            print(f"Error in upload_page: {str(e)}")
 
     if st.session_state.file_uploaded and st.button('View result'):
         if st.session_state.filename is None: