changes

app.py

@@ -4,6 +4,7 @@ import numpy as np
 from sklearn.linear_model import LinearRegression
 import matplotlib.pyplot as plt
 import io
+from PIL import Image
 
 def linear_regression(input_csv, x_column, y_column):
     # Load dataset from binary
@@ -28,15 +29,16 @@ def linear_regression(input_csv, x_column, y_column):
     plt.ylabel(y_column)
     plt.title('Linear Regression')
 
-    # Save plot to a buffer
+    # Save plot to a buffer and convert to PIL Image
     buf = io.BytesIO()
     plt.savefig(buf, format='png')
     buf.seek(0)
+    image = Image.open(buf)
 
     # Regression info
     coef_info = f"Coefficient: {model.coef_[0]}\nIntercept: {model.intercept_}"
 
-    return buf, coef_info
+    return image, coef_info
 
 # Gradio interface
 iface = gr.Interface(
@@ -47,7 +49,7 @@ iface = gr.Interface(
         gr.components.Textbox(label="Y Column Name"),
     ],
     outputs=[
-        gr.components.Image(type="plot"),
+        gr.components.Image(type="pil"),
         gr.components.Textbox(label="Regression Info")
     ],
     title="Automatic Linear Regression Modeling",