Commit c33d0f6b authored by Raj Gite's avatar Raj Gite
parents 603ce8d7 04ad370d
...@@ -14,6 +14,16 @@ ...@@ -14,6 +14,16 @@
"accelerator": "GPU" "accelerator": "GPU"
}, },
"cells": [ "cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "ZzS6OM-yfixt"
},
"source": [
"**Indian Dance Form Recognition using custom CNNs**<br>\n",
"This is a classification problem with 8 classes. In this task, we will be doing 7-fold cross validation on a training set of 364 images. This will be done using varied CNN networks. We will analyse the average accuracies from the cross-validation."
]
},
{ {
"cell_type": "code", "cell_type": "code",
"metadata": { "metadata": {
...@@ -46,16 +56,13 @@ ...@@ -46,16 +56,13 @@
] ]
}, },
{ {
"cell_type": "code", "cell_type": "markdown",
"metadata": { "metadata": {
"id": "hhb1KDmXALaF" "id": "pExcuhZqhHmq"
}, },
"source": [ "source": [
"!mkdir helpers\n", "You need to import the 'helpers' folder, it contains code for cross-validation, etc."
"!touch helpers/__init__.py" ]
],
"execution_count": null,
"outputs": []
}, },
{ {
"cell_type": "code", "cell_type": "code",
...@@ -83,37 +90,6 @@ ...@@ -83,37 +90,6 @@
"execution_count": null, "execution_count": null,
"outputs": [] "outputs": []
}, },
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mKkJU_yHSim-",
"outputId": "761133a1-4389-4e39-beaf-af864b8ff6d7"
},
"source": [
"import importlib\n",
"importlib.reload(helper)\n",
"importlib.reload(base_model)\n",
"importlib.reload(CV)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<module 'helpers.cross_validation' from '/content/helpers/cross_validation.py'>"
]
},
"metadata": {
"tags": []
},
"execution_count": 2
}
]
},
{ {
"cell_type": "code", "cell_type": "code",
"metadata": { "metadata": {
...@@ -197,7 +173,7 @@ ...@@ -197,7 +173,7 @@
"outputId": "485bce42-02c3-4d07-e2bd-538521c85c21" "outputId": "485bce42-02c3-4d07-e2bd-538521c85c21"
}, },
"source": [ "source": [
"###############Data Distributions##############\n", "############### Data Distributions for the 7 folds ##############\n",
"distribution_dict = {}\n", "distribution_dict = {}\n",
"ctr = 0\n", "ctr = 0\n",
"for i in image_labels:\n", "for i in image_labels:\n",
...@@ -794,6 +770,15 @@ ...@@ -794,6 +770,15 @@
} }
] ]
}, },
{
"cell_type": "markdown",
"metadata": {
"id": "mwlSHc5Wh4Qy"
},
"source": [
"As we can see, Model1, on average tends to perform relatively better."
]
},
{ {
"cell_type": "code", "cell_type": "code",
"metadata": { "metadata": {
......
This source diff could not be displayed because it is too large. You can view the blob instead.
**************INITIAL README************** **************README**************
#Change later
TEAM:
Aarushi Aiyyer - 203050045
Bhavesh Yadav - 193050052
Khyati Oswal - 203050058
Raj Gite - 203050092
Smit Gangurde - 203050108
Yavnika Bhagat - 203050041
Problem Statement:
Identify the type of Indian dance form from a dance pose image
Use multiple techniques to classify the images and compare them
Dataset Links: Dataset Links:
1) https://www.kaggle.com/somnath796/indian-dance-form-recognition #This is version 1, 27MB 1) https://www.kaggle.com/somnath796/indian-dance-form-recognition 27MB
2) https://www.kaggle.com/parthplc/indian-dance-images/version/2 #Version 2, 232MB
Conventions: Conventions:
- dataset1/ : Dataset Version 1 (Smaller size dataset) - dataset1/ : Dataset Version 1
- dataset2/ : Dataset Version 2 (Larger Size dataset)
Paper Links: Paper Links:
1) https://arxiv.org/pdf/1812.05231.pdf (IIT Delhi) 1) https://arxiv.org/pdf/1812.05231.pdf (IIT Delhi)
...@@ -15,22 +24,17 @@ Paper Links: ...@@ -15,22 +24,17 @@ Paper Links:
3) https://ieeexplore.ieee.org/document/9182365 3) https://ieeexplore.ieee.org/document/9182365
Helpful reference code: Helpful reference code:
1) https://github.com/ubsingh9/identify-the-dance-form 1)https://www.kaggle.com/singhuday/identifythedanceform/version/1
2)https://github.com/Tessellate-Imaging/monk_v1
3)https://clever-noyce-f9d43f.netlify.app/#/introduction
4)https://www.youtube.com/watch?v=zFA8Cm13Xmk
5)https://medium.com/@dtuk81/confusion-matrix-visualization-fc31e3f30fea
Added Dataset Version 1 to Google Drive: https://drive.google.com/file/d/1zTI002FEm0BcbXlUFpLs5zvurWGnx68v/view?usp=sharing Added Dataset Version 1 to Google Drive: https://drive.google.com/file/d/1zTI002FEm0BcbXlUFpLs5zvurWGnx68v/view?usp=sharing
Added Dataset Version 2 to Google Drive: https://drive.google.com/file/d/1I29xdtdJVd7FoT7Uyw1QHafKyRzsqPzK/view?usp=sharing
Reason: To make it easier to work on Google Colab. The Repository contains 3 notebooks:
---------------------------------------------------------------------------------- 1. Custom CNN
*******THIS IS PURELY FOR CONVENIENCE, TO SETUP THE DATASET ENV IN COLAB.******* 2. VGG16
*******YOU DO NOT NEED TO NECESSARILY FOLLOW THIS.******* 3. RESNET152
*******LINKS SUBJECT TO CHANGE AFTER PREPROCESSING.*******
----------------------------------------------------------------------------------
RUN THE FOLLOWING IN GOOGLE COLAB TO IMPORT FOLDERS:
----------------------------------------------------------------------------------
> !pip install gdown
> !gdown --id <insert id of file here>
#eg: !gdown --id 1I29xdtdJVd7FoT7Uyw1QHafKyRzsqPzK #for dataset2
> !tar -zxf <tar-filename>
> !rm <tar-filename>
----------------------------------------------------------------------------------
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