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import gradio as gr
import cv2
import requests
import os
from ultralytics import YOLO
path = ['./data/0068.jpg', './data/0210.jpg', './data/IMG_7078.jpg', './data/IMG_7103.jpg', './data/IMG_7705.jpg']
model_path = './best.pt'
model = YOLO(model_path)
def detect_cheerios(image_path):
# Run inference on the input image
results = model(image_path)
image = results[0].plot() [:,:,::-1]
return image
iface = gr.Interface(
fn=detect_cheerios,
inputs=gr.components.Image(type="filepath", label="Input Image"),
outputs=gr.Image(),
title="Cheerios detector",
description='Check out our blog at <a href="https://falcon.duality.ai/secure/documentation?learnWelcome=true&sidebarMode=learn" target="_blank">this link</a>.',
examples= path,
# gradio.HTML(https://falcon.duality.ai/secure/documentation?learnWelcome=true&sidebarMode=learn),
)
# Launch the interface
iface.launch()