louiecerv/cats_dogs_recognition_tf_nn
Image Classification • Updated • 1
Datasets:
Tasks:
Image Classification
Formats:
parquet
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
10K - 100K
License:
Search is not available for this dataset
image array 3D | label class label 2
classes |
|---|---|
[
[
[
40,
45,
41
],
[
41,
45,
45
],
[
40,
43,
48
],
[
53,
56,
63
],
[
41,
44,
48
],
[
42,
46,
46
],
[
39,
45,
41
],
[
35,
... | 0cats |
[[[29,33,42],[19,24,34],[31,34,48],[42,45,61],[41,45,59],[39,43,55],[45,49,61],[49,54,66],[50,57,68](...TRUNCATED) | 0cats |
[[[221,222,217],[223,224,219],[223,224,219],[222,223,218],[227,228,224],[230,229,232],[228,227,232],(...TRUNCATED) | 0cats |
[[[140,112,75],[141,113,76],[146,118,81],[150,122,84],[115,87,47],[106,78,39],[102,73,34],[136,108,6(...TRUNCATED) | 0cats |
[[[55,51,8],[58,48,18],[61,46,18],[62,48,14],[56,45,17],[37,28,16],[25,24,13],[24,23,14],[25,19,8],[(...TRUNCATED) | 0cats |
[[[158,123,104],[159,124,105],[158,123,104],[154,119,100],[152,117,98],[149,118,98],[149,120,99],[15(...TRUNCATED) | 0cats |
[[[170,167,174],[158,155,162],[167,166,174],[195,194,202],[191,192,201],[177,180,189],[167,170,180],(...TRUNCATED) | 0cats |
[[[11,6,3],[11,6,3],[12,7,4],[12,7,4],[12,6,3],[16,5,4],[20,9,8],[21,19,16],[24,22,15],[29,25,16],[3(...TRUNCATED) | 0cats |
[[[88,56,33],[88,56,33],[91,59,36],[94,62,38],[94,61,38],[60,38,24],[73,54,41],[96,65,44],[99,61,36](...TRUNCATED) | 0cats |
[[[129,129,119],[132,132,122],[136,136,126],[135,135,125],[136,137,126],[139,141,130],[141,143,132],(...TRUNCATED) | 0cats |
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Cats and Dogs Image Classification Dataset
This dataset contains images of cats and dogs, intended for image classification tasks. It includes two classes: "cats" and "dogs".
Dataset Structure
The dataset is structured into two splits:
- train: Contains 8000 images for training.
- test: Contains 2000 images for testing.
Images are stored in RGB format with a resolution of 128x128 pixels.
Data Loading and Usage
The dataset can be loaded using the Hugging Face Datasets library:
from datasets import load_dataset
dataset = load_dataset("cats_dogs_dataset")
This will return a DatasetDict object with the train and test splits.
Example Usage
Python
from datasets import load_dataset
dataset = load_dataset("cats_dogs_dataset")
# Access the first training example
example = dataset["train"]
# Print the image and label
print(example["image"])
print(example["label"])
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Models trained or fine-tuned on louiecerv/cats_dogs_dataset