Update app.py

app.py

@@ -1,36 +1,23 @@
-import os
-
-# Create the app folder if it doesn't exist
-os.makedirs('/content/BCCD-object/app', exist_ok=True)
-
-# Define the Gradio app code
-app_code = """
-import gradio as gr
-from ultralytics import YOLO
-from PIL import Image
-
-# Load the trained model
-model = YOLO('/content/BCCD-object/model/bccd_yolov8.pt')
-
-# Prediction function
-def predict(image):
-    results = model(image)
-    annotated_image = results[0].plot()  # Draw bounding boxes
-    return Image.fromarray(annotated_image)
-
-# Gradio Interface
-iface = gr.Interface(
-    fn=predict,
-    inputs=gr.Image(type="pil"),
-    outputs=gr.Image(type="pil"),
-    title="BCCD Object Detection",
-    description="Upload an image to detect RBC, WBC, and Platelets.",
-)
-
-# Launch the app
-iface.launch(share=True)
-"""
-
-# Save the code to app.py
-with open('/content/BCCD-object/app/app.py', 'w') as f:
-    f.write(app_code)
+import gradio as gr
+from ultralytics import YOLO
+from PIL import Image
+
+# Load the trained model
+model = YOLO('bccd_yolov8.pt')  # Make sure the model file is in the same folder as app.py
+
+# Prediction function
+def predict(image):
+    results = model(image)
+    annotated_image = results[0].plot()  # Draw bounding boxes
+    return Image.fromarray(annotated_image)
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="BCCD Object Detection",
+    description="Upload an image to detect RBC, WBC, and Platelets.",
+)
+
+iface.launch()