Refers:
http://www.cs.toronto.edu/~kriz/cifar.html
https://www.tensorflow.org/tutorials/deep_cnn
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes.
ClixSense Click on the cat job use the image that its size is 128 x 96 px, and
the image is cat or dog, no other type.
I want to use CNN to do machine learning for this job.
I collected some images now.
The key python codes to append one image with label to the dataset is as below:
from PIL import Image
import numpy as np
im = Image.open(filename)
im = (np.array(im))
r = im[:,:,0].flatten()
g = im[:,:,1].flatten()
b = im[:,:,2].flatten()
if iscat:
label = [0]
else:
label = [1]
out = np.array(list(label) + list(r) + list(g) + list(b), np.uint8)
out.tofile(dataset)
Subscribe to:
Post Comments (Atom)
fixed: embedded-redis: Unable to run on macOS Sonoma
Issue you might see below error while trying to run embedded-redis for your testing on your macOS after you upgrade to Sonoma. java.la...
-
Refer: https://github.com/bazelbuild/bazel/wiki/Building-with-a-custom-toolchain https://www.tensorflow.org/tutorials/image_recognition
-
F:\webrowser>react-native run-android Scanning folders for symlinks in F:\webrowser\node_modules (73ms) Starting JS server... Buildin...
-
Solution react-native bundle --platform android --dev false --entry-file index.js --bundle-output android/app/src/main/assets/index.android...
No comments:
Post a Comment