dev check working

app.py

@@ -86,8 +86,8 @@ class UnifiedDeepfakeDetector:
     def __init__(self):
         self.input_shape = (224, 224, 3)
         self.vgg_model = self.build_vgg16_model()
-        self.dense_model = tf.keras.models.load_model('file.h5')
-        self.cnn_model = tf.keras.models.load_model('file2.h5')
+        self.dense_model = tf.keras.models.load_model('./downloads/file.h5')
+        self.cnn_model = tf.keras.models.load_model('./downloads/file2.h5')
         self.melody_machine = pipeline(model="MelodyMachine/Deepfake-audio-detection-V2")
 
     def build_vgg16_model(self):
@@ -264,4 +264,35 @@ def classify_audio(features):
     if  entropy > 150:
         return True, entropy
     else:
-        return False, entropy
+        return False, entropy
+
+#--------------------------------------------------------------------------------------------------------------------
+from fastapi import FastAPI, File, UploadFile, Form
+from fastapi.responses import JSONResponse
+import torch
+from scipy.stats import skew, kurtosis, median_abs_deviation
+import shutil
+import subprocess
+import os
+import librosa
+
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
+os.environ["MPLCONFIGDIR"] = "/tmp/matplotlib"
+os.environ["FONTCONFIG_PATH"] = "/tmp/fontconfig"
+os.environ["HF_HOME"] = "/tmp/huggingface_cache"
+
+os.makedirs("/tmp/matplotlib", exist_ok=True)
+os.makedirs("/tmp/fontconfig", exist_ok=True)
+os.makedirs("/tmp/huggingface_cache", exist_ok=True)
+
+SAVE_DIR = './audio' 
+os.makedirs(SAVE_DIR, exist_ok=True)
+
+
+def reencode_audio(input_path, output_path):
+    command = [
+        'ffmpeg', '-i', input_path, '-acodec', 'pcm_s16le', '-ar', '16000', '-ac', '1', output_path
+    ]
+    subprocess.run(command, check=True)
+