Update app.py

app.py

@@ -5,39 +5,41 @@ import numpy as np
 from deepface import DeepFace
 
 # Define the folder path where images will be saved
-dataset_path = "/content/dataset"  # For Colab or your local environment
+dataset_path = "/content/dataset"  # For Colab, this will save in your Colab environment
+
+# Ensure the directory exists
 if not os.path.exists(dataset_path):
     os.makedirs(dataset_path)
 
-# Function to predict emotion and save the image
-def capture_and_recognize(image, name):
-    # Convert Gradio image (PIL format) to OpenCV image
+# Function to capture, save image, and predict emotion
+def capture_and_predict(image, name):
+    # Convert Gradio image (PIL format) to an OpenCV image
     img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
-
+    
     # Analyze the emotion using DeepFace
     result = DeepFace.analyze(img, actions=['emotion'])
     
     # Get the dominant emotion
     dominant_emotion = result[0]['dominant_emotion']
     
-    # Create a folder for each person if not exists
+    # Save the image with a timestamp in the dataset folder
     person_folder = os.path.join(dataset_path, name)
-    os.makedirs(person_folder, exist_ok=True)
+    os.makedirs(person_folder, exist_ok=True)  # Create a folder for each person if not exists
     
-    # Save the image in the person's folder
     image_count = len(os.listdir(person_folder))
     image_path = os.path.join(person_folder, f"{image_count + 1}.jpg")
-    cv2.imwrite(image_path, cv2.cvtColor(img, cv2.COLOR_RGB2BGR))  # Save in BGR format for OpenCV
+    cv2.imwrite(image_path, cv2.cvtColor(img, cv2.COLOR_BGR2RGB))  # Save the image in RGB format for consistency
     
     return f"Image saved for {name} with emotion: {dominant_emotion} at {image_path}"
 
 # Define the Gradio interface
 iface = gr.Interface(
-    fn=capture_and_recognize,
-    inputs=[gr.Image(type="pil", source="webcam"), gr.Textbox()],  # Webcam input and Name input
-    outputs="text",  # Text output for saved image path and emotion
-    title="Attendance Image Capture with Emotion Recognition",
-    description="Capture an image via webcam, enter your name, and the image will be saved with emotion recognition."
+    fn=capture_and_predict,
+    inputs=[gr.Image(type="pil"), gr.Textbox(label="Enter your name")],
+    outputs="text",
+    title="Capture and Predict Facial Emotion",
+    description="Capture an image from your webcam, enter your name, and the system will predict your emotion and save the image.",
+    live=True
 )
 
 # Launch the Gradio app