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import gradio as gr | |
from TheDistanceAssessor import run, load_segformer, load_yolo | |
def process_image(input_image): | |
image_size = [1024,1024] | |
target_distances = [650,1000,2000] | |
num_ys = 10 | |
PATH_model_seg = 'SegFormer_B3_1024_finetuned.pth' | |
PATH_model_det = 'yolov8s.pt' | |
model_seg = load_segformer(PATH_model_seg) | |
model_det = load_yolo(PATH_model_det) | |
output_image = run(input_image, model_seg, model_det, image_size, target_distances, num_ys = num_ys) | |
return output_image | |
# Create the Gradio interface | |
iface = gr.Interface( | |
fn=process_image, # The function to be called | |
inputs=gr.Image(type="pil"), # Input type | |
outputs=gr.Image(type="numpy"), # Output type | |
title="Image Processor", # Title of the interface | |
description="Upload an image and get a processed image as output." # Description of the interface | |
) | |
# Launch the interface | |
if __name__ == "__main__": | |
iface.launch() |