app.py

from openvino.runtime import Core
import gradio as gr 
import numpy as np 
from PIL import Image

def normalize(img):
  img=img.astype(np.float32)
  mean=(0.485, 0.456, 0.406)
  std=(0.229, 0.224, 0.225)
  img/=255.0
  img-=mean
  img/std
  return img
def segment_image(filepath):
  image=cv2.imread(filepath)
  image=cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
  image = cv2.resize(image, (512,512))
  x=tfms(image.copy()/255.)
  #ort_input={ort_session.get_inputs()[0].name:x.cpu().unsqueeze(0).float().numpy()}
  #out=ort_session.run(None,ort_input)
  out = compiled_model_onnx([x.unsqueeze(0).float().cpu().numpy()])
  pred_mask=np.squeeze(np.argmax(out[0],1)).astype(np.uint8)
  color_mask=cv2.applyColorMap(pred_mask,cv2.COLORMAP_MAGMA)*10
  masked_image=cv2.addWeighted(image,0.6,color_mask,0.4,0.1)
  return Image.fromarray(masked_image),Image.fromarray((color_mask))

demo=gr.Interface(fn=segment_image,inputs=gr.Image(type='filepath'),
                  outputs=[gr.Image(type="pil"),gr.Image(type="pil")],
                  examples=['/content/miccai2022_sisvse_dataset/images/real/R002_ch1_video_01_01-07-25-19.jpg',
                            "/content/miccai2022_sisvse_dataset/images/real/R003_ch1_video_01_01-14-13-15.jpg",
                            "/content/miccai2022_sisvse_dataset/images/real/R013_ch1_video_01_00-50-27-19.jpg",
                            "/content/miccai2022_sisvse_dataset/images/real/R010_ch1_video_03_00-26-28-05.jpg",
                            "/content/miccai2022_sisvse_dataset/images/real/R007_ch1_video_04_00-15-54-18.jpg",
                            "/content/miccai2022_sisvse_dataset/images/real/R013_ch1_video_03_00-55-16-10.jpg",
                            "/content/miccai2022_sisvse_dataset/images/real/R006_ch1_video_01_00-49-32-01.jpg",
                            "/content/miccai2022_sisvse_dataset/images/real/R005_ch1_video_03_00-18-54-00.jpg"],
                  themes=gr.themes.Soft(primary_hue=gr.themes.colors.amber,secondary_hue=gr.themes.colors.blue),
                  title="Davinci Eye(CPU version)")
demo.launch()