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import tempfile | |
import os | |
from PIL import Image | |
import gradio as gr | |
import paddlehub as hub | |
module = hub.Module(name="solov2") | |
def inference(img, threshold): | |
with tempfile.TemporaryDirectory() as tempdir_name: | |
module.predict(image=img, threshold=threshold, visualization=True, save_dir=tempdir_name) | |
result_names = os.listdir(tempdir_name) | |
output_image = Image.open(os.path.join(tempdir_name, result_names[0])) | |
return [output_image] | |
title="SOLOv2" | |
description="SOLOv2 is a fast instance segmentation model based on paper \"SOLOv2: Dynamic, Faster and Stronger\". The model improves the detection performance and efficiency of masks compared to SOLOv1, and performs well in instance segmentation tasks." | |
gr.Interface(inference,inputs=[gr.inputs.Image(type="filepath"),gr.Slider(0.0, 1.0, value=0.5)],outputs=gr.Gallery(label="Detection Result"),title=title,description=description).launch(enable_queue=True) |