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import gradio as gr
import cv2
from geti_sdk.deployment import Deployment
from geti_sdk.utils import show_image_with_annotation_scene
#Load the deployment
deployment = Deployment.from_folder("deployment")
deployment.load_inference_models(device="CPU")
def resize_image(image, target_dimension):
height, width = image.shape[:2]
max_dimension = max(height, width)
scale_factor = target_dimension / max_dimension
new_width = int(width * scale_factor)
new_height = int(height * scale_factor)
resized_image = cv2.resize(image, (new_width, new_height))
return resized_image
def infer(image=None):
if image is None:
return [None,'Error: No image provided']
image = resize_image(image, 1200)
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
prediction = deployment.infer(image_rgb)
output = show_image_with_annotation_scene(image, prediction, show_results=False)
output = cv2.cvtColor(output, cv2.COLOR_RGB2BGR)
return [output, prediction.overview]
def run():
demo = gr.Interface(fn=infer,
inputs=['image'],
outputs=['image', 'text'],
examples=[["no_bird.jpg"], ["bird_example1.jpg"], ["bird_example2.jpg"], ["bird_example3.jpg"]])
demo.launch(server_name="0.0.0.0", server_port=7860)
if __name__ == "__main__":
run()
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