Archive for the 'Python' Category

What Object Categories / Labels Are In COCO Dataset?

One important element of deep learning and machine learning at large is dataset. A good dataset will contribute to a model with good precision and recall. In the realm of object detection in images or motion pictures, there are some household names commonly used and referenced by researchers and practitioners. The names in the list include Pascal, ImageNet, SUN, and COCO. In this post, we will briefly discuss about COCO dataset, especially on its distinct feature and labeled objects.

tl;dr The COCO dataset labels from the original paper and the released versions in 2014 and 2017 can be viewed and downloaded from this repository. Continue reading

Resolving Error “ImportError: No module name named hypothesis”

When running the test script “relu_op_test.py” to verify Caffe2 installation, you may encounter this error “ImportError: No module name named hypothesis”. Let’s take a look at the content of the script to get some idea about the root cause.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

from caffe2.python import core
from hypothesis import given
import hypothesis.strategies as st
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.mkl_test_util as mu
import numpy as np

import unittest

class TestRelu(hu.HypothesisTestCase):

    @given(X=hu.tensor(),
           engine=st.sampled_from(["", "CUDNN"]),
           **mu.gcs)
    def test_relu(self, X, gc, dc, engine):
        op = core.CreateOperator("Relu", ["X"], ["Y"], engine=engine)
        # go away from the origin point to avoid kink problems
        X += 0.02 * np.sign(X)
        X[X == 0.0] += 0.02
        self.assertDeviceChecks(dc, op, [X], [0])
        self.assertGradientChecks(gc, op, [X], 0, [0])


if __name__ == "__main__":
    unittest.main()

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