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import gradio as gr | |
from ultralytics import YOLO | |
from sahi.prediction import ObjectPrediction | |
from sahi.utils.cv import visualize_object_predictions, read_image | |
from gradio.components import Slider, Image, Dropdown | |
def yolov8_inference( | |
image: Image = None, | |
model_path: Dropdown = None, | |
image_size: Slider = 640, | |
confidence_threshold: Slider = 0.25, | |
iou_threshold: Slider = 0.45, | |
): | |
model = YOLO(model_path) | |
model.conf = confidence_threshold | |
model.iou = iou_threshold | |
results = model.predict(image, imgsz=image_size) | |
object_prediction_list = [] | |
for _, image_results in enumerate(results): | |
if len(image_results) != 0: | |
image_predictions_in_xyxy_format = image_results.boxes.data | |
for pred in image_predictions_in_xyxy_format: | |
x1, y1, x2, y2 = ( | |
int(pred[0]), | |
int(pred[1]), | |
int(pred[2]), | |
int(pred[3]), | |
) | |
bbox = [x1, y1, x2, y2] | |
score = pred[4] | |
category_name = model.model.names[int(pred[5])] | |
category_id = pred[5] | |
object_prediction = ObjectPrediction( | |
bbox=bbox, | |
category_id=int(category_id), | |
score=score, | |
category_name=category_name, | |
) | |
object_prediction_list.append(object_prediction) | |
output_image = visualize_object_predictions(image=image, object_prediction_list=object_prediction_list) | |
return output_image['image'] | |
inputs = [ | |
"image", | |
Dropdown(label="Model", choices=["yolo/runs/detect/train10/weights/best.pt"], value="yolo/runs/detect/train10/weights/best.pt", visible=False), | |
Slider(minimum=320, maximum=1280, step=32, value=640, label="Image Size"), | |
Slider(minimum=0.0, maximum=1.0, step=0.05, value=0.45, label="Confidence Threshold"), | |
Slider(minimum=0.0, maximum=1.0, step=0.05, value=0.25, label="IOU Threshold"), | |
] | |
title = "Smartathon Pothole Challenge" | |
examples = [ | |
["examples/0014.png", "yolo/runs/detect/train10/weights/best.pt", 640, 0.45, 0.25], | |
["examples/0055.png", "yolo/runs/detect/train10/weights/best.pt", 640, 0.45, 0.25], | |
["examples/0083.png", "yolo/runs/detect/train10/weights/best.pt", 640, 0.45, 0.25], | |
] | |
iface = gr.Interface( | |
fn=yolov8_inference, | |
inputs=inputs, | |
outputs="image", | |
title=title, | |
examples=examples, | |
theme="default", | |
) | |
iface.launch(debug=True) | |