File size: 4,166 Bytes
6deaaa7 4236061 fcb7a64 05777f7 04eb9b3 c09ea63 04eb9b3 ac8096b 04eb9b3 ac8096b 04eb9b3 88f2538 e8e40de 88f2538 e8e40de 88f2538 e8e40de |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
---
license: apache-2.0
language:
- de
- en
metrics:
- accuracy
- roc_auc
library_name: tf-keras
pipeline_tag: image-classification
---
# Brain tumor classification using CNN
<!-- Provide a quick summary of what the model is/does.
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
-->
## Model Details
### Model Description
```python
model.summary()
Out:
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
rescaling (Rescaling) (None, 200, 200, 1) 0
conv2d (Conv2D) (None, 200, 200, 16) 160
max_pooling2d (MaxPooling2D (None, 100, 100, 16) 0
)
conv2d_1 (Conv2D) (None, 100, 100, 32) 4640
max_pooling2d_1 (MaxPooling (None, 50, 50, 32) 0
2D)
conv2d_2 (Conv2D) (None, 50, 50, 64) 18496
max_pooling2d_2 (MaxPooling (None, 25, 25, 64) 0
2D)
flatten (Flatten) (None, 40000) 0
dense (Dense) (None, 128) 5120128
dense_1 (Dense) (None, 64) 8256
dense_2 (Dense) (None, 128) 8320
dense_3 (Dense) (None, 64) 8256
dense_4 (Dense) (None, 32) 2080
dense_5 (Dense) (None, 96) 3168
dense_6 (Dense) (None, 96) 9312
dense_7 (Dense) (None, 128) 12416
dense_8 (Dense) (None, 1) 129
=================================================================
Total params: 5,195,361
Trainable params: 5,195,361
Non-trainable params: 0
_________________________________________________________________
```
### Dataset
The dataset is composed of [Brain Tumor Classification (MRI)](https://www.kaggle.com/datasets/sartajbhuvaji/brain-tumor-classification-mri) and
[Brain MRI Images for Brain Tumor Detection](https://www.kaggle.com/datasets/navoneel/brain-mri-images-for-brain-tumor-detection)
Using image data augmentation we get 199.632 files belonging to 2 classes.
train-test-split: 80/20
Training (159705 files):
- Using 143735 files for training
- Using 15970 files for validation
Test/Validation:
- 39927 files
### Training
Coming Soon
### Validation
Coming Soon
#### Hardware
Lenovo Thinkpad P14s
- CPU (# Cores/Threads): AMD Ryzen 7 PRO 5850U (8/16)
- RAM: 32 GB
#### Software
DataSpell 2023.1.2
- Python 3.10.9
- Tensorflow 2.12.0 |