Update README.md

README.md

@@ -6,4 +6,43 @@ datasets:
 - imagenet-1k
 ---
 
-See: https://huggingface.co/timm/edgenext_small.usi_in1k
+See: https://huggingface.co/timm/edgenext_small.usi_in1k
+
+```python
+from urllib.request import urlopen
+
+import einops
+import numpy as np
+import onnxruntime as ort
+from PIL import Image
+
+def softmax(x):
+    y = np.exp(x - np.max(x))
+    return y / y.sum(axis=0)
+
+IMG_URL = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
+IN1K_CLASSES_URL = 'https://storage.googleapis.com/bit_models/ilsvrc2012_wordnet_lemmas.txt'
+
+session = ort.InferenceSession('edgenext_small.usi_in1k.ort')
+# session = ort.InferenceSession('edgenext_small.usi_in1k.onnx')
+
+labels = urlopen(IN1K_CLASSES_URL).read().decode().splitlines()
+img = np.array(
+    Image.open(urlopen(IMG_URL))
+    .resize(session._sess.inputs_meta[0].shape[2:])
+)
+
+# e.g. in1k norm stats
+mean = .485, .456, .406
+sd = .229, .224, .225
+img = (img / 255. - mean) / sd
+
+# to clearly illustrate format ort expects
+img = einops.rearrange(img, 'h w c -> 1 c h w').astype(np.float32)
+out = session.run(None, {session.get_inputs()[0].name: img})
+
+out = softmax(out[0][0])
+topk = np.argsort(out)[::-1][:5]
+for i in topk:
+    print(f'{out[i]:.2f}', labels[i])
+```