Update app.py

app.py

@@ -49,35 +49,7 @@ def predict_emotion_from_audio(wav_filepath):
         return None
 
 api_key = os.getenv("DeepAI_api_key")
-# Define the API key for DeepAI Text to Image API
-#api_key = 'dee3e3f2-d5cf-474c-8072-bd6bea47e865'
 
-####
-import torch
-from transformers import Speech2TextProcessor, Speech2TextForConditionalGeneration
-
-
-# Load the pretrained model and processor
-model = Speech2TextForConditionalGeneration.from_pretrained("facebook/s2t-small-librispeech-asr")
-processor = Speech2TextProcessor.from_pretrained("facebook/s2t-small-librispeech-asr")
-
-# Load your local audio file
-#audio_input, sampling_rate = sf.read("/content/1001_IEO_DIS_HI.wav")
-
-# Convert the audio to PyTorch tensors using the processor
-inputs = processor(audio_input, sampling_rate=sampling_rate, return_tensors="pt")
-
-# Generate transcription in English
-generated_ids = model.generate(
-    inputs["input_features"],
-    attention_mask=inputs["attention_mask"],
-    forced_bos_token_id=processor.tokenizer.bos_token_id  # Use the <s> token ID as the start of sequence token
-)
-
-# Decode the generated transcription
-transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)
-
-###
 
 # Predict emotion from audio
 def get_predictions(audio_input):
@@ -86,13 +58,6 @@ def get_predictions(audio_input):
     image = generate_image(api_key, emotion_prediction)
     return emotion_prediction, image
 
-    
-
-###
-
-
-
-
 
 # Define a function to generate an image using DeepAI Text to Image API
 def generate_image(api_key, text):