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- #!/usr/bin/env python3
- import numpy as np
- import cv2
- import megengine.data.transform as T
- import megengine.functional as F
- import json
- import urllib
- url, filename = ("https://data.megengine.org.cn/images/cat.jpg", "input_data/cat.jpg")
- try: urllib.URLopener().retrieve(url, filename)
- except: urllib.request.urlretrieve(url, filename)
-
- # numpy data
- data=np.random.rand(1,3,224,224)
- np.save("input_data/resnet50_input_uint8.npy",data.astype(np.uint8))
- np.save("input_data/resnet50_input.npy",data.astype(np.float32))
-
- #ppm data
- image = cv2.imread("input_data/cat.jpg")
- transform = T.Compose([
- T.Resize(256),
- T.CenterCrop(224),
- ])
- processed_img = transform.apply(image)
- cv2.imwrite("input_data/cat.ppm",processed_img)
-
- #json
- data_obj = {
- "shape": [1,3],
- "type": "float32",
- "raw": [2,3,4]
- }
- with open("input_data/add_demo_input.json", "w") as f:
- json.dump({"data":data_obj},f)
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