FEAT: Preload deepface model from repository

src/streamlit_app.py

@@ -1,7 +1,5 @@
 import os
 import streamlit as st
-# Point the cache directory to the guaranteed writable /tmp folder
-os.environ['DEEPFACE_HOME'] = '/tmp/.deepface'
 import numpy as np
 import torch
 import whisper
@@ -13,19 +11,43 @@ import tempfile
 import cv2
 from moviepy.editor import VideoFileClip
 import time
+import shutil # Import the shutil library for file copying
 
-# Create a cross-platform, writable cache directory for all libraries
+# --- Create a cross-platform, writable cache directory for all libraries ---
 CACHE_DIR = os.path.join(tempfile.gettempdir(), "affectlink_cache")
 os.makedirs(CACHE_DIR, exist_ok=True)
 os.environ['DEEPFACE_HOME'] = CACHE_DIR
 os.environ['HF_HOME'] = CACHE_DIR
 
+# === THIS IS THE NEW CODE TO PRELOAD THE DEEPFACE MODEL ===
+# Define paths for the pre-included model weights
+MODEL_NAME = "facial_expression_model_weights.h5"
+SOURCE_PATH = os.path.join("src", "weights", MODEL_NAME)
+DEST_DIR = os.path.join(CACHE_DIR, ".deepface", "weights")
+DEST_PATH = os.path.join(DEST_DIR, MODEL_NAME)
+
+# Create the destination directory if it doesn't exist and copy the model
+if not os.path.exists(DEST_PATH):
+    print(f"Model not found in cache. Copying from {SOURCE_PATH} to {DEST_PATH}...")
+    os.makedirs(DEST_DIR, exist_ok=True)
+    try:
+        shutil.copy(SOURCE_PATH, DEST_PATH)
+        print("Model copied successfully.")
+    except FileNotFoundError:
+        print(f"Warning: Local model file not found at {SOURCE_PATH}. App will attempt to download it.")
+    except Exception as e:
+        print(f"Error copying model file: {e}")
+# =========================================================
+
 # --- Page Configuration ---
 st.set_page_config(page_title="AffectLink Demo", page_icon="😊", layout="wide")
 st.title("AffectLink: Post-Hoc Emotion Analysis")
 st.write("Upload a short video clip (under 30 seconds) to analyze facial expressions, speech-to-text, and the emotional tone of the audio.")
 
 # --- Logger Configuration ---
+# [The rest of your code remains the same]
+# [I have included the full script below for clarity]
+
 logging.basicConfig(level=logging.INFO)
 logging.getLogger('deepface').setLevel(logging.ERROR)
 logging.getLogger('huggingface_hub').setLevel(logging.WARNING)

src/weights/facial_expression_model_weights.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8e8851d3fa05c001b1c27fd8841dfe08d7f82bb786a53ad8776725b7a1e824c
+size 5977392