Spaces:
Runtime error
Runtime error
File size: 2,536 Bytes
df95879 8a764fa df95879 8a764fa df95879 8a764fa 90cbf36 8a764fa 90cbf36 8a764fa 90cbf36 8a764fa |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
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)
|