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import gradio as gr
from PIL import Image
import numpy as np
from ultralytics import YOLO
import os
def handle_classify(image=None):
"""This function performs YOLOv8 object detection on the given image.
Args:
image (gr.inputs.Image, optional): Input image to detect objects on. Defaults to None.
"""
model_path = "racistv4.pt"
model = YOLO(model_path)
results = model(image)
result = results[0]
top5 = [[result.names[class_index], str(round(result.probs.top5conf.tolist()[rank], 4)*100)+'%']
for class_index, rank in zip(result.probs.top5, range(5))]
print(top5)
return "\n".join(['{:<16}:{:>8}'.format(row[0], row[1]) for row in top5])
inputs = [
gr.Image(label="Input Image"),
]
outputs = gr.Textbox()
title = "Racist model v4"
SAMPLE_DIR = 'samples'
examples = [os.path.join(SAMPLE_DIR, path) for path in os.listdir(SAMPLE_DIR)]
yolo_app = gr.Interface(
fn=handle_classify,
inputs=inputs,
outputs=outputs,
title=title,
examples=examples,
cache_examples=True,
)
# Launch the Gradio interface in debug mode with queue enabled
yolo_app.launch(debug=True) |