add app

app.py

@@ -8,7 +8,7 @@ import os
 model = tf.keras.models.load_model("car_brand_classifier_final.h5")
 
 # Define the path to the dataset containing car brand folders
-DATASET_PATH = "./Car_Sales_vision_ai_project"
+DATASET_PATH = "car_sales_images"
 
 # Get the list of car brands (folder names) in the dataset
 CAR_BRANDS = sorted(os.listdir(DATASET_PATH))
@@ -64,7 +64,7 @@ iface = gr.Interface(
     inputs=gr.Image(type="numpy"),  # Ensure Gradio passes a NumPy array
     outputs=[
         gr.Textbox(label="Predicted Brand"),
-        gr.Gallery(label="Sample Images").style(grid=[5], height="auto")  # Display images in a gallery
+        gr.Gallery(label="Sample Images")  # Display images in a gallery
     ],
     title="Car Vision",
     description="Upload an image of a car to classify its brand and view sample images."