Update app.py

app.py

@@ -2,17 +2,16 @@ import gradio as gr
 import pandas as pd
 import numpy as np
 import joblib
-import os
 from skimage.measure import shannon_entropy
 from skimage.color import rgb2hsv
 from scipy.ndimage import generic_filter
 import cv2
+from PIL import Image
 
 # Function to extract features from the image
-def extract_features(image_path):
-    # Load image and convert to RGB
-    image = cv2.imread(image_path)
-    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+def extract_features(image):
+    # Convert PIL image to NumPy array
+    image = np.array(image)
     
     # Extract RGB means
     meanr = np.mean(image[:, :, 0])  # Red channel
@@ -76,12 +75,12 @@ def extract_features(image_path):
 # Function to check if the image is a valid file format
 def check_image_format(image):
     try:
-        img = cv2.imread(image)
-        if img is not None:
-            return True
-        else:
-            return False
+        # Try opening the image using PIL
+        img = Image.open(image)
+        img.verify()  # Verify if it's a valid image file
+        return True
     except Exception as e:
+        print(f"Error opening image: {e}")
         return False
 
 # Function to predict hemoglobin value
@@ -96,14 +95,14 @@ def predict_hemoglobin(age, gender, image):
     features = extract_features(image)
     
     # Ensure gender is encoded correctly (0 for female, 1 for male)
-    features['Gender'] = 1 if gender.lower() == 'M' else 0
+    features['Gender'] = 1 if gender.lower() == 'male' else 0
     features['Age'] = age
     
     # Create a DataFrame for features (do not include Hgb, as it's the predicted value)
     features_df = pd.DataFrame([features])
 
     # Load the trained model, scaler, and label encoder
-    svr_model = joblib.load('svr_model (1).pkl')
+    svr_model = joblib.load('svr_model(1).pkl')
     scaler = joblib.load('minmax_scaler.pkl')
     label_encoder = joblib.load('label_encoder.pkl')
 
@@ -127,7 +126,7 @@ def predict_hemoglobin(age, gender, image):
 # Gradio Interface setup
 def create_gradio_interface():
     # Define the inputs and outputs for the Gradio interface
-    image_input = gr.Image(type="filepath", label="Image (Path to Image)", interactive=True)
+    image_input = gr.Image(type="pil", label="Image (Upload Image)", interactive=True)
     age_input = gr.Number(label="Age", value=25, precision=0)
     gender_input = gr.Radio(choices=["Male", "Female"], label="Gender", value="Male")