Load model from local directory instead of Hugging Face Hub

app.py

@@ -32,8 +32,8 @@ import gradio as gr
 
 # ========== CONFIGURATION ==========
 
-# Hugging Face model ID
-HF_MODEL_ID = os.getenv("HF_MODEL_ID", "Meet2304/convnextv2-cervical-cell-classification")
+# Model directory (local path relative to this file)
+MODEL_DIR = os.path.join(os.path.dirname(__file__), "convnextv2_cervical_v0.1")
 
 # Class names
 CLASS_NAMES = [
@@ -58,16 +58,16 @@ DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
 # ========== MODEL LOADING ==========
 
-print("Loading model from Hugging Face...")
-print(f"Model ID: {HF_MODEL_ID}")
+print("Loading model from local directory...")
+print(f"Model directory: {MODEL_DIR}")
 print(f"Device: {DEVICE}")
 
 # Load image processor
-processor = AutoImageProcessor.from_pretrained(HF_MODEL_ID)
+processor = AutoImageProcessor.from_pretrained(MODEL_DIR)
 print("✓ Processor loaded")
 
 # Load model
-model = ConvNextV2ForImageClassification.from_pretrained(HF_MODEL_ID)
+model = ConvNextV2ForImageClassification.from_pretrained(MODEL_DIR)
 model = model.to(DEVICE)
 model.eval()
 print("✓ Model loaded and set to evaluation mode")

requirements.txt

@@ -1,8 +1,8 @@
 torch>=2.0.0
 torchvision>=0.15.0
 transformers>=4.30.0
-gradio==4.0.0
-opencv-python-headless==4.8.1.78
-numpy~=1.24.0
-Pillow>=10.0.0,<11.0.0
+gradio>=4.0.0
+opencv-python>=4.8.0
+numpy>=1.24.0
+Pillow>=10.0.0
 grad-cam>=1.4.8