.

Streamlit-Image-Annotation.zip

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3fac0d3825299fcc1e946a7bcf9ddb23c351f1a7bcfbbf504b2ed447f22ebecb
-size 104629368

modules/train.py

@@ -1,7 +1,5 @@
 import copy
-import cv2
 import numpy as np
-import random
 import time
 import torch
 import torchvision.transforms.functional as F
@@ -9,8 +7,6 @@ import matplotlib.pyplot as plt
 
 from modules.eval import main_evaluation
 from torch.optim import SGD, AdamW
-from torch.utils.data import DataLoader, Dataset, Subset, ConcatDataset
-from torch.utils.data.dataloader import default_collate
 from torchvision.models.detection import keypointrcnn_resnet50_fpn, KeypointRCNN_ResNet50_FPN_Weights
 from torchvision.models.detection.faster_rcnn import FastRCNNPredictor
 from torchvision.models.detection.keypoint_rcnn import KeypointRCNNPredictor

modules/utils.py

@@ -11,12 +11,6 @@ from torch.utils.data.dataloader import default_collate
 import cv2
 import matplotlib.pyplot as plt
 from torch.utils.data import DataLoader, Subset, ConcatDataset
-from tqdm import tqdm
-from torch.optim import SGD
-import time
-from torch.optim import AdamW
-import copy
-from torchvision import transforms
 import streamlit as st
 
 

setup.sh

@@ -1,7 +0,0 @@
-#!/bin/bash
-
-# Unzip the package
-unzip -o Streamlit-Image-Annotation.zip -d Streamlit-Image-Annotation
-
-# Install the package in editable mode
-pip install -e ./Streamlit-Image-Annotation