Spaces:
Runtime error
Runtime error
File size: 1,275 Bytes
9f2b3ad ff5810a 9f2b3ad 54b3f5b 53e5c1f |
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 |
import gradio as gr
import torch
import torchvision
import numpy as np
from PIL import Image
# Load model weights
model = torch.hub.load('ultralytics/yolov5', 'custom', "model_weights/datasets_1000_41class.pt")
# Define a yolo prediction function
def yolo(im, size=640):
g = (size / max(im.size)) # gain
im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS) # resize
results = model(im) # inference
results.render() # updates results.imgs with boxes and labels
return Image.fromarray(results.imgs[0])
inputs = gr.inputs.Image(type='pil', label="Original Image")
outputs = gr.outputs.Image(type="pil", label="Output Image")
title = "BandiCount: Detecting Australian native animal species"
description = "BandiCount: Detecting Australian native animal species in NSW national parks, using object detection. Upload an image or click an example image to use."
article = ""
examples = [['data/BrushtailPossum.jpg'], ['data/Eagle.jpg'], ['data/Macropod.jpg'], ['data/cat.jpg'], ['data/echidna.gif'], ['data/fantail.png'], ['data/ibis.jpg'], ['data/koala1.jpeg'], ['data/koala2.jpg']]
gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples, theme="huggingface").launch(enable_queue=True)
|