Fixes the python example...

I missed the onnx model loading, silly me

README.md

@@ -33,13 +33,18 @@ import onnxruntime
 import numpy as np
 from PIL import Image
 
+model = onnxruntime.InferenceSession("deeplabv3p-resnet50-human.onnx")
+
 img = Image.open(sys.argv[1] if len(sys.argv) > 1 else "image.jpg")
 img = img.resize((512, 512))
 img = np.array(img).astype(np.float32) / 127.5 - 1
 
+# infer
 input_name = model.get_inputs()[0].name
 output_name = model.get_outputs()[0].name
 result = model.run([output_name], {input_name: img})
+
+# squeeze, argmax...
 result = np.array(result[0])
 # argmax the classes, remove the batch size
 result = result.argmax(axis=3).squeeze(0)