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import gradio as gr
import requests
from transformers import pipeline
from PIL import Image, ImageDraw
import numpy as np
obj_detector = pipeline(
"object-detection", model="bninaos/finetuned-ViT-model",
device = 'cpu')
def plot_results(image, results, threshold=0.7):
results = obj_detector(image)
image = Image.fromarray(np.uint8(image))
draw = ImageDraw.Draw(image)
for result in results:
score = result["score"]
label = result["label"]
box = list(result["box"].values())
if score > threshold:
x, y, x2, y2 = tuple(box)
draw.rectangle((x, y, x2, y2), outline="red", width=1)
draw.text((x, y), label, fill="white")
draw.text(
(x + 0.5, y - 0.5),
text=str(score),
fill="green" if score > threshold else "red",
)
return image
iface = gr.Interface(
fn=plot_results,
inputs=gr.Image(type="pil"),
outputs=gr.Image(type="pil"),
title="Hardhat Detection",
description="Upload an image to detect hardhats.",
)
iface.launch(share = True)
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