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import gradio as gr | |
from ultralytics import YOLO | |
import cv2 | |
from PIL import Image | |
import numpy as np | |
# Load YOLOv8 model | |
MODEL_PATH = "Best_Model1.pt" | |
model = YOLO(MODEL_PATH) | |
def detect_flash(image: Image.Image): | |
# Convert PIL image to OpenCV format | |
image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) | |
# Run detection | |
results = model(image_cv) | |
detections = results[0].boxes.data.tolist() | |
num_detections = len(detections) | |
message = "" | |
if num_detections > 0: | |
message += f"Flash(es) Detected: {num_detections}\n" | |
for i, det in enumerate(detections): | |
x1, y1, x2, y2, conf, cls = det | |
message += f" Flash {i+1}: Confidence={conf:.2f}, Position=[{int(x1)},{int(y1)},{int(x2)},{int(y2)}]\n" | |
else: | |
message = "No Flash Detected." | |
# Plot result | |
res_plotted = results[0].plot() | |
res_rgb = cv2.cvtColor(res_plotted, cv2.COLOR_BGR2RGB) | |
output_image = Image.fromarray(res_rgb) | |
return output_image, message | |
def clear_all(): | |
return None, None, "" | |
# Gradio interface | |
with gr.Blocks() as demo: | |
gr.Markdown("Flash Detection with YOLOv8") | |
gr.Markdown("Upload an image to detect flash.") | |
with gr.Row(): | |
img_input = gr.Image(type="pil", label="Upload Image") | |
output_img = gr.Image(type="pil", label="Detected Image") | |
output_text = gr.Textbox(label="Detection Info", lines=6) | |
with gr.Row(): | |
detect_btn = gr.Button("Detect Flash") | |
clear_btn = gr.Button("Clear") | |
detect_btn.click(fn=detect_flash, inputs=img_input, outputs=[output_img, output_text]) | |
clear_btn.click(fn=clear_all, inputs=[], outputs=[img_input, output_img, output_text]) | |
demo.launch() |