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import gradio as gr
import cv2
import requests
import os
from PIL import Image
import torch
import ultralytics
model = torch.hub.load("ultralytics/yolov5", "custom", path="yolov5_0.65map_exp7_best.pt",
force_reload=False)
model.conf = 0.20 # NMS confidence threshold
path = [['img/test-image.jpg']]
def show_preds_image(im):
results = model(im) # inference
return results.render()[0]
inputs_image = [
gr.components.Image(type="filepath", label="Input Image"),
]
outputs_image = [
gr.components.Image(type="filepath", label="Output Image"),
]
interface_image = gr.Interface(
fn=show_preds_image,
inputs=inputs_image,
outputs=outputs_image,
title="Cashew Disease Detection",
examples=path,
cache_examples=False,
)
interface_image.launch() |