fixed tthe error

features/image_classifier/model_loader.py

@@ -1,29 +1,21 @@
 import os
 import shutil
 import logging
-import tensorflow as tf
-from tensorflow.keras.layers import Layer
 from huggingface_hub import snapshot_download
 from config import Config
 
+os.environ.setdefault("CUDA_VISIBLE_DEVICES", "-1")
+os.environ.setdefault("TF_CPP_MIN_LOG_LEVEL", "2")
+
 # Model config
 REPO_ID = Config.IMAGE_CLASSIFIER_REPO_ID
 MODEL_DIR = Config.IMAGE_CLASSIFIER_MODEL_DIR
 WEIGHTS_PATH = os.path.join(MODEL_DIR, Config.IMAGE_CLASSIFIER_WEIGHTS_FILE)
 HF_TOKEN = Config.HF_TOKEN
 
-# Device info (for logging)
-gpus = tf.config.list_physical_devices("GPU")
-device = "cuda" if gpus else "cpu"
-
 # Global model reference
 _model_img = None
 
-# Custom layer used in the model
-class Cast(Layer):
-    def call(self, inputs):
-        return tf.cast(inputs, tf.float32)
-
 def warmup():
     global _model_img
     download_model_repo()
@@ -43,11 +35,17 @@ def load_model():
     if _model_img is not None:
         return _model_img
 
-    print(f"{'GPU detected' if device == 'cuda' else 'No GPU detected'}, loading model on {device.upper()}.")
+    import tensorflow as tf
+
+    class Cast(tf.keras.layers.Layer):
+        def call(self, inputs):
+            return tf.cast(inputs, tf.float32)
 
-    _model_img = tf.keras.models.load_model(
-        WEIGHTS_PATH, custom_objects={"Cast": Cast}
-    )
+    print("Loading image model on CPU.")
+    with tf.device("/CPU:0"):
+        _model_img = tf.keras.models.load_model(
+            WEIGHTS_PATH, custom_objects={"Cast": Cast}
+        )
     print("Model input shape:", _model_img.input_shape)
     return _model_img
 

features/real_forged_classifier/main.py

@@ -1,26 +0,0 @@
-from fastapi import FastAPI
-from routes import router as api_router
-
-# Initialize the FastAPI app
-app = FastAPI(
-    title="Real vs. Fake Image Classification API",
-    description="An API to classify images as real or forged using FFT and cnn.",
-    version="1.0.0"
-)
-
-# Include the API router
-# All routes defined in routes.py will be available under the /api prefix
-app.include_router(api_router, prefix="/api", tags=["Classification"])
-
-@app.get("/", tags=["Root"])
-async def read_root():
-    """
-    A simple root endpoint to confirm the API is running.
-    """
-    return {"message": "Welcome to the Image Classification API. Go to /docs for the API documentation."}
-
-# To run this application:
-# 1. Make sure you have all dependencies from requirements.txt installed.
-# 2. Make sure the 'svm_model.joblib' file is in the same directory.
-# 3. Run the following command in your terminal:
-#    uvicorn main:app --reload