Upload 4 files

classes.json

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+{"train": 0, "seaplane": 1, "motorbus": 2, "airplane": 3, "stair": 4, "bicycle": 5, "bus": 6, "car": 7, "crosswalk": 8, "hydrant": 9, "motorcycle": 10, "mountain": 11, "stairs": 12, "tow truck": 13, "traffic light": 14, "traffic sign": 15, "truck": 16}

example.py

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+
+# ONNX for image classification model
+
+import onnxruntime as ort
+import numpy
+from PIL import Image
+
+ort_sess = ort.InferenceSession('model.onnx')
+classes = [ "train" ,  "seaplane" ,  "motorbus" ,  "airplane" ,  "stair" ,  "bicycle" ,  "bus" ,  "car" ,  "crosswalk" ,  "hydrant" ,  "motorcycle" ,  "mountain" ,  "stairs" ,  "tow truck" ,  "traffic light" ,  "traffic sign" ,  "truck" , ]
+
+img = Image.open("image.jpg").convert('RGB')
+img = img.resize((300, 300 * img.size[1] // img.size[0]), Image.ANTIALIAS)
+inp_numpy = numpy.array(img)[None].astype('float32')
+
+
+class_scores = ort_sess.run(None, {'input': inp_numpy})[0][0]
+
+
+
+print("")
+print("class_scores", class_scores)
+print("Class : ", classes[class_scores.argmax()])

model.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:75b984b8df7c427254966dfd08b057a96f11adc01894772a37109463449552f0
+size 16196546