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import gradio as gr
from gradio.outputs import Label
import cv2
import requests
import os
from ultralytics import YOLO
file_urls = [
'https://www.dropbox.com/s/b5g97xo901zb3ds/pothole_example.jpg?dl=1',
'https://www.dropbox.com/s/86uxlxxlm1iaexa/pothole_screenshot.png?dl=1'
]
def download_file(url, save_name):
url = url
if not os.path.exists(save_name):
file = requests.get(url)
open(save_name, 'wb').write(file.content)
for i, url in enumerate(file_urls):
download_file(
file_urls[i],
f"image_{i}.jpg"
)
model = YOLO('best.pt')
path = [['image_0.jpg'], ['image_1.jpg']]
def show_preds_image(image_path):
image = cv2.imread(image_path)
outputs = model.predict(source=image_path)
results = outputs[0].cpu().numpy()
for i, det in enumerate(results.boxes.xyxy):
# print(det.xyxy)
cv2.rectangle(
image,
(int(det[0]), int(det[1])),
(int(det[2]), int(det[3])),
color=(0, 0, 255),
thickness=2,
lineType=cv2.LINE_AA
)
return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
inputs_image = [
gr.components.Image(type="filepath", label="Input Image"),
# gr.components.Video(type="filepath", label="Input Video", optional=True),
]
outputs_image = [
gr.components.Image(type="numpy", label="Output Image"),
]
interface_image = gr.Interface(
fn=show_preds_image,
inputs=inputs_image,
outputs=outputs_image,
title="Pothole detector",
examples=path,
cache_examples=False,
# live=True,
)
inputs_video = [
gr.components.Video(type="filepath", label="Input Video"),
]
outputs_video = [
gr.components.Video(type="mp4", label="Output Image"),
]
interface_video = gr.Interface(
fn=show_preds_image,
inputs=inputs_video,
outputs=outputs_video,
title="Pothole detector",
examples=path,
cache_examples=False,
# live=True,
)
# interface_image.launch(debug=True, enable_queue=True)
gr.TabbedInterface([interface_image, interface_video]).launch() |