Update run.py

run.py

@@ -1,8 +1,17 @@
 import gradio as gr
 import numpy as np
 from time import sleep
+import torch
+from transformers import SegformerImageProcessor
 
-def flip_periodically(im, interval_ms=100):
+image_processor = SegformerImageProcessor(reduce_labels=True)
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.load_state_dict(torch.load(weights2load, weights_only=True, map_location=device))
+model.to(device).eval()
+
+
+def flip_periodically(im, interval_ms=0):
     """
     Flips the image periodically with the given interval.
 
@@ -13,13 +22,18 @@ def flip_periodically(im, interval_ms=100):
     Returns:
         The flipped image.
     """
+    pixel_values = image_processor(image, return_tensors="pt").pixel_values.to(device)
+    outputs = model(pixel_values=pixel_values)
+    logits = outputs.logits.cpu()
     sleep(interval_ms / 1000)  # Convert milliseconds to seconds
-    return np.flipud(im)
+    return logits[0, 0]  #np.flipud(im)
 
 with gr.Blocks() as demo:
     inp = gr.Image(sources=["webcam"], streaming=True)
     out = gr.Image()
     inp.stream(flip_periodically, inputs=inp, outputs=out) 
 
+
 if __name__ == "__main__":
+
     demo.launch()