Update app.py

app.py

@@ -1,11 +1,60 @@
 import gradio as gr
 from textblob import TextBlob
+from deepface import DeepFace
+import moviepy.editor as mp
+import cv2
+import tempfile
+import os
 
-def analyze(text):
+# Function to analyze text
+def analyze_text(text):
     blob = TextBlob(text)
     polarity = blob.sentiment.polarity
     sentiment = "Positive" if polarity > 0 else "Negative" if polarity < 0 else "Neutral"
-    return f"Sentiment: {sentiment} (Polarity: {polarity:.2f})"
+    return f"Text Sentiment: {sentiment} (Polarity: {polarity:.2f})"
 
-iface = gr.Interface(fn=analyze, inputs="text", outputs="text")
-iface.launch()
+# Function to analyze image (face emotion)
+def analyze_image(image):
+    try:
+        result = DeepFace.analyze(image, actions=['emotion'], enforce_detection=False)
+        dominant_emotion = result[0]['dominant_emotion']
+        return f"Detected Emotion: {dominant_emotion}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Function to analyze video (face emotion at center frame)
+def analyze_video(video_file):
+    try:
+        tmpdir = tempfile.mkdtemp()
+        clip = mp.VideoFileClip(video_file)
+        frame = clip.get_frame(clip.duration / 2)
+        frame_path = os.path.join(tmpdir, "frame.jpg")
+        cv2.imwrite(frame_path, cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))
+        result = DeepFace.analyze(frame_path, actions=['emotion'], enforce_detection=False)
+        dominant_emotion = result[0]['dominant_emotion']
+        return f"Video Emotion: {dominant_emotion}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 🧠 Emotion and Sentiment Analyzer")
+    with gr.Tab("Text Analysis"):
+        text_input = gr.Textbox(label="Enter Text")
+        text_output = gr.Textbox(label="Sentiment Result")
+        text_btn = gr.Button("Analyze Text")
+        text_btn.click(analyze_text, inputs=text_input, outputs=text_output)
+
+    with gr.Tab("Image Analysis"):
+        img_input = gr.Image(type="filepath", label="Upload Face Image")
+        img_output = gr.Textbox(label="Emotion Result")
+        img_btn = gr.Button("Analyze Image")
+        img_btn.click(analyze_image, inputs=img_input, outputs=img_output)
+
+    with gr.Tab("Video Analysis"):
+        video_input = gr.Video(label="Upload Face Video")
+        video_output = gr.Textbox(label="Emotion Result")
+        video_btn = gr.Button("Analyze Video")
+        video_btn.click(analyze_video, inputs=video_input, outputs=video_output)
+
+demo.launch()