abhicodes commited on
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6d04fe9
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1 Parent(s): ddeb95f

Update app.py

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Files changed (1) hide show
  1. app.py +17 -13
app.py CHANGED
@@ -9,7 +9,10 @@ from transformers import pipeline
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  API_KEY = os.getenv("API_KEY")
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- API_URL = "https://api-inference.huggingface.co/models/dima806/facial_emotions_image_detection"
 
 
 
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  headers = {"Authorization": "Bearer "+ API_KEY+""}
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  reader = easyocr.Reader(['en'], gpu=False)
@@ -22,7 +25,7 @@ def query(image):
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  _, buffer = cv2.imencode('.jpg', image_data)
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  binary_data = buffer.tobytes()
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- response = requests.post(API_URL, headers=headers, data=binary_data)
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  result = {item['label']: item['score'] for item in response.json()}
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  return result
@@ -42,12 +45,11 @@ def text_extraction(image):
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  return image, text_content, facial_data
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  def analyze_sentiment(text):
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- results = sentiment_analysis(text)
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- sentiment_results = {result['label']: result['score'] for result in results}
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  return sentiment_results
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  def get_sentiment_emoji(sentiment):
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- # Define the emojis corresponding to each sentiment
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  emoji_mapping = {
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  "disappointment": "😞",
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  "sadness": "😒",
@@ -182,15 +184,17 @@ with block:
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  gr.Textbox(label="Text Content")
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  output_text_sentiment = gr.Textbox(label="Text Sentiment")
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-
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- audio = gr.Audio(label="Input Audio", show_label=False, type="filepath")
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-
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- with gr.Row():
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- sentiment_option = gr.Radio(choices=["Sentiment Only", "Sentiment + Score"], label="Select an option")
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- lang_str = gr.Textbox(label="Language")
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- text = gr.Textbox(label="Transcription")
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- sentiment_output = gr.Textbox(label="Audio Text Sentiment")
 
 
 
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  btn = gr.Button("Run")
 
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  API_KEY = os.getenv("API_KEY")
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+ IMAGE_API_URL = "https://api-inference.huggingface.co/models/dima806/facial_emotions_image_detection"
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+ headers = {"Authorization": "Bearer "+ API_KEY+""}
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+
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+ EMOTIONS_API_URL = "https://api-inference.huggingface.co/models/SamLowe/roberta-base-go_emotions"
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  headers = {"Authorization": "Bearer "+ API_KEY+""}
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  reader = easyocr.Reader(['en'], gpu=False)
 
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  _, buffer = cv2.imencode('.jpg', image_data)
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  binary_data = buffer.tobytes()
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+ response = requests.post(IMAGE_API_URL, headers=headers, data=binary_data)
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  result = {item['label']: item['score'] for item in response.json()}
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  return result
 
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  return image, text_content, facial_data
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  def analyze_sentiment(text):
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+ results = requests.post(EMOTIONS_API_URL, headers=headers, json=text)
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+ sentiment_results = {result['label']: result['score'] for result in results.json()}
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  return sentiment_results
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  def get_sentiment_emoji(sentiment):
 
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  emoji_mapping = {
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  "disappointment": "😞",
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  "sadness": "😒",
 
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  gr.Textbox(label="Text Content")
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  output_text_sentiment = gr.Textbox(label="Text Sentiment")
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+
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+ with gr.Blocks():
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+ with gr.Row():
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+ audio = gr.Audio(label="Input Audio", show_label=False, type="filepath")
 
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+ with gr.Row():
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+ sentiment_option = gr.Radio(choices=["Sentiment Only", "Sentiment + Score"], label="Select an option")
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+
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+ lang_str = gr.Textbox(label="Language")
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+ text = gr.Textbox(label="Transcription")
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+ sentiment_output = gr.Textbox(label="Audio Text Sentiment")
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  btn = gr.Button("Run")