Please pay attention to these notes:
Assignment Page: https://iust-deep-learning.github.io/981/assignments/02_image_task_and_visualization
Course Forum: https://groups.google.com/forum/#!forum/dl981/
Fill your information here & run the cell
#@title Enter your information & "RUN the cell!!" { run: "auto" }
student_id = 0 #@param {type:"integer"}
student_name = "" #@param {type:"string"}
Your_Github_account_Email = "" #@param {type:"string"}
print("your student id:", student_id)
print("your name:", student_name)
from pathlib import Path
ASSIGNMENT_PATH = Path('asg02')
ASSIGNMENT_PATH.mkdir(parents=True, exist_ok=True)
Consider the public transport bus service. It has many gates on roads in the city and a particular lane for bus transportation.
This lane is also used for the transportation of emergency vehicles like ambulances, police cars and fire trucks, and private cars are banned from using it.
Your task is to create a system to classify these two classes of vehicles.
Please explain your dataset making method.
$\color{red}{\text{Write your answer here}}$
Build and train your model in the following cell.
Use generator and augmentation in order to feed data to the network.
Now, test your model, report the f1-score, recall and precision, and then save the model in a file with path 'ASSIGNMENT_PATH / 'my_model.h5''.
Plot loss and accuracy.
Please explain that what type of loss and accuracy you set for training your model and why?
$\color{red}{\text{Write your answer here}}$
Visualize some layers and analyze them.
$\color{red}{\text{Write your answer here}}$
Congratulations! You finished the assignment & you're ready to submit your work. Please follow the instruction:
dl_asg02__xx__xx.zip) and submit it via https://forms.gle/Fb7gvVJHp8RePvo6A.Note: We need your Github token to create (if doesn't exist previously) new repository to store learned model data. Also Google Drive token enables us to download the current notebook & create a submission. If you are interested feel free to check our code.
#@title
! pip install -U --quiet PyDrive > /dev/null
! wget -q https://github.com/github/hub/releases/download/v2.10.0/hub-linux-amd64-2.10.0.tgz
import os
import time
import yaml
import json
from google.colab import files
from IPython.display import Javascript
from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
from google.colab import auth
from oauth2client.client import GoogleCredentials
asg_name = 'assignment_02'
script_save = '''
require(["base/js/namespace"],function(Jupyter) {
Jupyter.notebook.save_checkpoint();
});
'''
repo_name = 'iust-deep-learning-assignments'
submission_file_name = 'dl_asg02__%s__%s.zip'%(student_id, student_name.lower().replace(' ', '_'))
! tar xf hub-linux-amd64-2.10.0.tgz
! cd hub-linux-amd64-2.10.0/ && chmod a+x install && ./install
! hub config --global hub.protocol https
! hub config --global user.email "$Your_Github_account_Email"
! hub config --global user.name "$student_name"
! hub api --flat -X GET /user
! hub api -F affiliation=owner -X GET /user/repos > repos.json
repos = json.load(open('repos.json'))
repo_names = [r['name'] for r in repos]
has_repository = repo_name in repo_names
if not has_repository:
get_ipython().system_raw('! hub api -X POST -F name=%s /user/repos > repo_info.json' % repo_name)
repo_info = json.load(open('repo_info.json'))
repo_url = repo_info['clone_url']
else:
for r in repos:
if r['name'] == repo_name:
repo_url = r['clone_url']
stream = open("/root/.config/hub", "r")
token = list(yaml.load_all(stream))[0]['github.com'][0]['oauth_token']
repo_url_with_token = 'https://'+token+"@" +repo_url.split('https://')[1]
! git clone "$repo_url_with_token"
! cp -r "$ASSIGNMENT_PATH" "$repo_name"/
! cd "$repo_name" && git add -A
! cd "$repo_name" && git commit -m "Add assignment 02 results"
! cd "$repo_name" && git push -u origin master
sub_info = {
'student_id': student_id,
'student_name': student_name,
'repo_url': repo_url,
'asg_dir_contents': os.listdir(str(ASSIGNMENT_PATH)),
'dateime': str(time.time()),
'asg_name': asg_name
}
json.dump(sub_info, open('info.json', 'w'))
Javascript(script_save)
auth.authenticate_user()
gauth = GoogleAuth()
gauth.credentials = GoogleCredentials.get_application_default()
drive = GoogleDrive(gauth)
file_id = drive.ListFile({'q':"title='%s.ipynb'"%asg_name}).GetList()[0]['id']
downloaded = drive.CreateFile({'id': file_id})
downloaded.GetContentFile('%s.ipynb'%asg_name)
! jupyter nbconvert --to script "$asg_name".ipynb > /dev/null
! jupyter nbconvert --to html "$asg_name".ipynb > /dev/null
! zip "$submission_file_name" "$asg_name".ipynb "$asg_name".html "$asg_name".txt info.json > /dev/null
print("##########################################")
print("Done! Submisson created, Please download using the bellow cell!")
#@title
files.download(submission_file_name)
If that cell makes an error when running you can download file dl_asg02_your_struden_id_your_name.zip from left panel and files section by right-clicking on it and choosing download button.
Special thanks to Amirhossein Kazemnejad and Kiamehr Razaee for creating the template of deep learning course assignments.