Create app.py

app.py

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+import streamlit as st
+import cv2
+import numpy as np
+from PIL import Image
+import tempfile
+import time
+
+class DogLanguageInterpreter:
+    def __init__(self):
+        # Initialize any models or configurations here
+        self.emotions = {
+            'tail_wagging': 'Happy and excited',
+            'ears_perked': 'Alert and interested',
+            'lying_down': 'Relaxed or tired',
+            'barking': 'Trying to communicate',
+            'jumping': 'Enthusiastic and playful'
+        }
+    
+    def analyze_video(self, video_file):
+        # Placeholder for video analysis logic
+        # In a real implementation, this would use CV models
+        return {
+            'primary_emotion': 'Happy and excited',
+            'confidence': 0.85,
+            'actions_detected': ['tail_wagging', 'jumping'],
+            'recommendations': [
+                'Your dog seems very playful!',
+                'Consider engaging in some active play',
+                'Reward this positive energy with treats'
+            ]
+        }
+
+def main():
+    st.set_page_config(
+        page_title="Dog Language Interpreter",
+        page_icon="🐕",
+        layout="wide"
+    )
+
+    # Header
+    st.title("🐕 Pet Dog Language Understanding")
+    st.markdown("""
+    Upload a video of your dog, and our AI will help interpret their behavior and emotions!
+    """)
+
+    # Initialize interpreter
+    interpreter = DogLanguageInterpreter()
+
+    # File uploader
+    video_file = st.file_uploader("Upload a video of your dog", type=['mp4', 'mov', 'avi'])
+
+    if video_file:
+        # Save video to temporary file
+        tfile = tempfile.NamedTemporaryFile(delete=False)
+        tfile.write(video_file.read())
+
+        # Display video
+        st.video(tfile.name)
+
+        # Analysis button
+        if st.button("Analyze Dog Behavior"):
+            with st.spinner("Analyzing your dog's behavior..."):
+                # Simulate processing time
+                time.sleep(2)
+                
+                # Get analysis results
+                results = interpreter.analyze_video(tfile.name)
+
+                # Display results in columns
+                col1, col2 = st.columns(2)
+
+                with col1:
+                    st.subheader("Primary Emotion")
+                    st.info(results['primary_emotion'])
+                    st.metric("Confidence", f"{results['confidence']*100:.1f}%")
+
+                with col2:
+                    st.subheader("Actions Detected")
+                    for action in results['actions_detected']:
+                        st.success(action.replace('_', ' ').title())
+
+                # Recommendations
+                st.subheader("Recommendations")
+                for rec in results['recommendations']:
+                    st.write("• " + rec)
+
+    # Additional information
+    with st.expander("About Dog Body Language"):
+        st.markdown("""
+        ### Common Dog Behaviors and Their Meanings:
+        - **Tail Wagging**: Usually indicates happiness, but the position matters
+        - **Ears Position**: Can show alertness, submission, or aggression
+        - **Body Posture**: Reveals confidence or anxiety levels
+        - **Facial Expressions**: Can indicate stress, happiness, or attention
+        
+        Remember that each dog is unique and may express emotions differently!
+        """)
+
+if __name__ == "__main__":
+    main()