Code revision

api.py

@@ -4,9 +4,10 @@ from PIL import Image, UnidentifiedImageError, ImageFile
 from io import BytesIO
 from db import bytes_to_megabytes
 from pillow_heif import register_heif_opener
+import os
 
 @st.cache_data(show_spinner=True) 
-def fetchAssets(immich_server_url, api_key, timeout):
+def fetchAssets(immich_server_url, api_key, timeout, type):
     # Initialize messaging and progress
     if 'fetch_message' not in st.session_state:
         st.session_state['fetch_message'] = ""
@@ -29,7 +30,7 @@ def fetchAssets(immich_server_url, api_key, timeout):
             if 'application/json' in content_type:
                 if response.text:
                     assets = response.json()  # Decode JSON response into a list of assets
-                    assets = [asset for asset in assets if asset.get("type") == "IMAGE"]                       
+                    assets = [asset for asset in assets if asset.get("type") == type]                       
                     st.session_state['fetch_message'] = 'Assets fetched successfully!'
                 else:
                     st.session_state['fetch_message'] = 'Received an empty response.'
@@ -53,8 +54,7 @@ def fetchAssets(immich_server_url, api_key, timeout):
     message_placeholder.text(st.session_state['fetch_message'])
     return assets
 
-#@st.cache_data(show_spinner=True)
-def streamAsset(asset_id, immich_server_url,photo_choice,api_key):   
+def getImage(asset_id, immich_server_url,photo_choice,api_key):   
     # Determine whether to fetch the original or thumbnail based on user selection
     register_heif_opener()
     ImageFile.LOAD_TRUNCATED_IMAGES = True
@@ -183,4 +183,25 @@ def updateAsset(immich_server_url, asset_id, api_key, dateTimeOriginal, descript
     except requests.RequestException as e:
         st.error(f"Request failed: {str(e)}")
         print(f"Request failed: {str(e)}")
-        return False
+        return False
+    
+#For video function
+def getVideoAndSave(asset_id, immich_server_url,api_key,save_directory):   
+    # Ensure the directory exists
+    if not os.path.exists(save_directory):
+        os.makedirs(save_directory)
+
+    response = requests.get(f"{immich_server_url}/api/download/asset/{asset_id}", headers={'Accept': 'application/octet-stream', 'x-api-key': api_key}, stream=True)
+    file_path = os.path.join(save_directory, f"{asset_id}.mp4")
+
+    if response.status_code == 200 and 'video/' in response.headers.get('Content-Type', ''):
+        try:
+            with open(file_path, 'wb') as f:
+                f.write(response.content)
+            return file_path
+        except Exception as e:
+            print(f"Failed to save video for asset_id {asset_id}. Error: {e}")
+            return None
+    else:
+        print(f"Failed to retrieve video for asset_id {asset_id}. Status Code: {response.status_code}, Content-Type: {response.headers.get('Content-Type')}")
+        return None

app.py

@@ -91,13 +91,14 @@ def configure_sidebar():
         st.markdown(f"**Version:** {program_version}\n\n{additional_data}")
 
 def main():
+    #print(fetchAssets(immich_server_url, api_key,timeout, 'VIDEO'))
     setup_session_state()
     configure_sidebar()
     assets = None
 
     # Attempt to fetch assets if any asset-related operation is to be performed
     if st.session_state['calculate_faiss'] or st.session_state['generate_db_duplicate'] or st.session_state['show_faiss_duplicate']:
-        assets = fetchAssets(immich_server_url, api_key,timeout)
+        assets = fetchAssets(immich_server_url, api_key,timeout, 'IMAGE')
         if not assets:
             st.error("No assets found or failed to fetch assets.")
             return  # Stop further execution since there are no assets to process

imageDuplicate.py

@@ -8,7 +8,7 @@ import faiss
 from torchvision.models import resnet152, ResNet152_Weights
 from torchvision.transforms import Compose, Resize, ToTensor, Normalize
 
-from api import streamAsset
+from api import getImage
 from utility import display_asset_column
 from api import getAssetInfo
 from db import load_duplicate_pairs, is_db_populated, save_duplicate_pair
@@ -63,7 +63,7 @@ def update_faiss_index(immich_server_url,api_key, asset_id):
     if asset_id in existing_metadata:
         return 'skipped'  # Skip processing this image
 
-    image = streamAsset(asset_id, immich_server_url, "Thumbnail (fast)", api_key)
+    image = getImage(asset_id, immich_server_url, "Thumbnail (fast)", api_key)
     if image is not None:
         features = extract_features(image)
     else:
@@ -216,9 +216,9 @@ def show_duplicate_photos_faiss(assets, limit, min_threshold, max_threshold,immi
                 progress_bar.progress(progress)
 
                 asset_id_1, asset_id_2 = dup_pair
-                # Assuming `streamAsset` and `getAssetInfo` are defined elsewhere in your code
-                image1 = streamAsset(asset_id_1, immich_server_url, 'Thumbnail (fast)', api_key)
-                image2 = streamAsset(asset_id_2, immich_server_url, 'Thumbnail (fast)', api_key)
+
+                image1 = getImage(asset_id_1, immich_server_url, 'Thumbnail (fast)', api_key)
+                image2 = getImage(asset_id_2, immich_server_url, 'Thumbnail (fast)', api_key)
                 asset1_info = getAssetInfo(asset_id_1, assets)
                 asset2_info = getAssetInfo(asset_id_2, assets)
 

videoDuplicate.py

@@ -0,0 +1,26 @@
+import streamlit as st
+import time
+import os
+import torch
+import numpy as np
+import faiss
+from torchvision.models import resnet152, ResNet152_Weights
+from torchvision.transforms import Compose, Resize, ToTensor, Normalize
+
+from api import getVideo
+
+# Set the environment variable to allow multiple OpenMP libraries
+os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
+
+# Load ResNet152 with pretrained weights
+model = resnet152(weights=ResNet152_Weights.DEFAULT)
+model.eval()  # Set model to evaluation mode
+transform = Compose([
+    Resize((224, 224)),  # Standard size for ImageNet-trained models
+    ToTensor(),
+    Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
+])
+
+# Global variables for paths
+index_path = 'video_faiss_index.bin'
+metadata_path = 'video_metadata.npy'