From 90a257c13365e79e216d03dded2acba22de7f03d Mon Sep 17 00:00:00 2001 From: Devarsh Shah Date: Sat, 8 Jun 2024 19:51:22 +0530 Subject: [PATCH] Specifying project directories --- .../Dataset/Readme.md | 3 + .../Images/auto_test/0/9003175_1.png | Bin 0 -> 26037 bytes .../Images/auto_test/1/9001400_1.png | Bin 0 -> 23397 bytes .../Images/auto_test/2/9003316_1.png | Bin 0 -> 21341 bytes .../Images/auto_test/3/9011053_2.png | Bin 0 -> 25283 bytes .../Images/auto_test/4/9012867_1.png | Bin 0 -> 18793 bytes .../Images/test/0/9003175L.png | Bin 0 -> 25332 bytes .../Images/test/1/9001400L.png | Bin 0 -> 24307 bytes .../Images/test/2/9003316R.png | Bin 0 -> 21285 bytes .../Images/test/3/9011053L.png | Bin 0 -> 24328 bytes .../Images/test/4/9012867R.png | Bin 0 -> 18618 bytes .../Images/train/0/9001695L.png | Bin 0 -> 18797 bytes .../Images/train/1/9000622L.png | Bin 0 -> 17141 bytes .../Images/train/2/9000099R.png | Bin 0 -> 19055 bytes .../Images/train/3/9000099L.png | Bin 0 -> 18178 bytes .../Images/train/4/9025994L.png | Bin 0 -> 24639 bytes .../Images/val/0/9006140L.png | Bin 0 -> 18649 bytes .../Images/val/1/9003380L.png | Bin 0 -> 18843 bytes .../Images/val/2/9015402R.png | Bin 0 -> 24206 bytes .../Images/val/3/9023348L.png | Bin 0 -> 18212 bytes .../Images/val/4/9070207R.png | Bin 0 -> 17892 bytes Knee Osteoarthritis Prediction/Readme.md | 57 ++++++++++++++++++ 22 files changed, 60 insertions(+) create mode 100644 Knee Osteoarthritis Prediction/Dataset/Readme.md create mode 100644 Knee Osteoarthritis Prediction/Images/auto_test/0/9003175_1.png create mode 100644 Knee Osteoarthritis Prediction/Images/auto_test/1/9001400_1.png create mode 100644 Knee Osteoarthritis Prediction/Images/auto_test/2/9003316_1.png create mode 100644 Knee Osteoarthritis Prediction/Images/auto_test/3/9011053_2.png create mode 100644 Knee Osteoarthritis Prediction/Images/auto_test/4/9012867_1.png create mode 100644 Knee Osteoarthritis Prediction/Images/test/0/9003175L.png create mode 100644 Knee Osteoarthritis Prediction/Images/test/1/9001400L.png create mode 100644 Knee Osteoarthritis Prediction/Images/test/2/9003316R.png create mode 100644 Knee Osteoarthritis Prediction/Images/test/3/9011053L.png create mode 100644 Knee Osteoarthritis Prediction/Images/test/4/9012867R.png create mode 100644 Knee Osteoarthritis Prediction/Images/train/0/9001695L.png create mode 100644 Knee Osteoarthritis Prediction/Images/train/1/9000622L.png create mode 100644 Knee Osteoarthritis Prediction/Images/train/2/9000099R.png create mode 100644 Knee Osteoarthritis Prediction/Images/train/3/9000099L.png create mode 100644 Knee Osteoarthritis Prediction/Images/train/4/9025994L.png create mode 100644 Knee Osteoarthritis Prediction/Images/val/0/9006140L.png create mode 100644 Knee Osteoarthritis Prediction/Images/val/1/9003380L.png create mode 100644 Knee Osteoarthritis Prediction/Images/val/2/9015402R.png create mode 100644 Knee Osteoarthritis Prediction/Images/val/3/9023348L.png create mode 100644 Knee Osteoarthritis Prediction/Images/val/4/9070207R.png create mode 100644 Knee Osteoarthritis Prediction/Readme.md diff --git a/Knee Osteoarthritis Prediction/Dataset/Readme.md b/Knee Osteoarthritis Prediction/Dataset/Readme.md new file mode 100644 index 000000000..94836fc65 --- /dev/null +++ b/Knee Osteoarthritis Prediction/Dataset/Readme.md @@ -0,0 +1,3 @@ +The link for the dataset used in this project: https://www.kaggle.com/datasets/shashwatwork/knee-osteoarthritis-dataset-with-severity/data + +The dataset consists of four subdirectories: train, test, auto test and val (test and auto_test are the same). All four contain 5 subdirectories, each representing a severity of osteoarthritis. 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same). All four contain 5 subdirectories, each representing a severity of osteoarthritis. The test and auto_test subdirectory contains 1346 images in total, while the train subdirectory contains 5778 images in total and the val subdirectory contains 826 images in total. + +### ๐Ÿงพ **Description** + +The project deals with multi-class classification, classifying images into 5 grades of severity. + +### ๐Ÿงฎ **What I had done!** + +To achieve our goals, the following steps were implemented: + +- Images were loaded using keras.utils and normalized to the range 0 to 1. + +- Images were resized to a fixed size of 224x224 pixels. + +- Custom and pre-trained models were used for this task. + +### ๐Ÿš€ **Models Implemented** + +models used: + +- ResNet-50 +- Xception +- VGG16 +- CNN-Keras +- InceptionV3 +- DenseNet-121 +- EfficientNetB7 + +### ๐Ÿ“š **Libraries Needed** + +- Keras + +- Tensorflow + +- Numpy + +- Matplotlib + +We used Validation and Testing **Loss** and **Accuracy** as metrics. + +| Models | Accuracy | Loss | +|--------|---------------------|--------------------------| +| ResNet-50 | % | | +| InceptionV3 | % | | +| CNN | % | | +| VGG16 | % | | +| EfficientNetB7 | % | | +| DenseNet-121 | % | | +| Xception | % | | \ No newline at end of file