HuichuanLiu commented on issue #11149: Unreasonable performance of resnext models provided in model_zoo, evaluated by score.py URL: https://github.com/apache/incubator-mxnet/issues/11149#issuecomment-395677991 Agree, and It might involve not only the symbol definition, the pretrain params and the training process, but probably mismatch between the model and the scoring procedure, like the preprocess? FYI, I attempted to implement a gluon version resnext-101-64x4d based on the provided symbol file and restored param values from the provided checkpoint, this work ended at around acc=0.47+. with preprocess like: ``` def mx_preprocess(img, ctx): # img_cvt = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) img_nd = mx.nd.array(img) img_resize = mx.image.resize_short(src=img_nd, size=256) img_crop, _ = mx.image.center_crop(src=img_resize, size=(224, 224)) img_trans = mx.nd.transpose(img_crop, [2, 0, 1]) img_reshape = img_trans.reshape((1, 3, 224, 224)) return mx.nd.array(img_reshape, ctx=ctx) ``` Since resNeXt is quite new in the model_zoo, a re-evaluation could be very helpful.
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