Upload 3 files

app.py

@@ -0,0 +1,25 @@
+from ultralytics import YOLO
+import gradio as gr
+from PIL import Image
+import numpy as np
+
+# Load the trained YOLOv8 model
+model = YOLO("yolov8_license_plate.pt")  # Path where you uploaded the model
+
+# Define prediction function
+def detect_objects(image):
+    results = model(image)  # Perform inference
+    result_img = results[0].plot()  # Draw bounding boxes
+    return Image.fromarray(result_img.astype(np.uint8))  # Ensure correct image format
+
+# Build Gradio interface
+interface = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.Image(type="pil", label="Upload Image"),
+    outputs=gr.Image(type="pil", label="Detected Image"),
+    title="License Plate Detection (YOLOv8)",
+    description="Upload an image. The model will detect license plates using YOLOv8."
+)
+
+# Launch the interface
+interface.launch(debug=True)

requirements.txt

@@ -0,0 +1,3 @@
+ultralytics
+gradio
+pillow

yolov8_license_plate.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d40a3545ad6233df455577e0235ec863da1f89b998e46098a07d2d15d6651fb7
+size 6248227