added detection image and bounding boxes to run on bag

2023-03-21 12:03:10 +05:30
parent a312c2ae7d
commit fc5dbd85d3
145 changed files with 23 additions and 6 deletions
@@ -1,18 +0,0 @@
-#!/bin/bash
-# YOLOv3 🚀 by Ultralytics, GPL-3.0 license
-# Download latest models from https://github.com/ultralytics/yolov3/releases
-# Example usage: bash path/to/download_weights.sh
-# parent
-# └── yolov3
-#     ├── yolov3.pt  ← downloads here
-#     ├── yolov3-spp.pt
-#     └── ...
-
-python - <<EOF
-from utils.downloads import attempt_download
-
-models = ['yolov3', 'yolov3-spp', 'yolov3-tiny']
-for x in models:
-    attempt_download(f'{x}.pt')
-
-EOF
@@ -1,27 +0,0 @@
-#!/bin/bash
-# YOLOv3 🚀 by Ultralytics, GPL-3.0 license
-# Download COCO 2017 dataset http://cocodataset.org
-# Example usage: bash data/scripts/get_coco.sh
-# parent
-# ├── yolov3
-# └── datasets
-#     └── coco  ← downloads here
-
-# Download/unzip labels
-d='../datasets' # unzip directory
-url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
-f='coco2017labels.zip' # or 'coco2017labels-segments.zip', 68 MB
-echo 'Downloading' $url$f ' ...'
-curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
-
-# Download/unzip images
-d='../datasets/coco/images' # unzip directory
-url=http://images.cocodataset.org/zips/
-f1='train2017.zip' # 19G, 118k images
-f2='val2017.zip'   # 1G, 5k images
-f3='test2017.zip'  # 7G, 41k images (optional)
-for f in $f1 $f2; do
-  echo 'Downloading' $url$f '...'
-  curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
-done
-wait # finish background tasks
@@ -1,17 +0,0 @@
-#!/bin/bash
-# YOLOv3 🚀 by Ultralytics, GPL-3.0 license
-# Download COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
-# Example usage: bash data/scripts/get_coco128.sh
-# parent
-# ├── yolov3
-# └── datasets
-#     └── coco128  ← downloads here
-
-# Download/unzip images and labels
-d='../datasets' # unzip directory
-url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
-f='coco128.zip' # or 'coco128-segments.zip', 68 MB
-echo 'Downloading' $url$f ' ...'
-curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
-
-wait # finish background tasks
@@ -1,51 +0,0 @@
-#!/bin/bash
-# YOLOv3 🚀 by Ultralytics, GPL-3.0 license
-# Download ILSVRC2012 ImageNet dataset https://image-net.org
-# Example usage: bash data/scripts/get_imagenet.sh
-# parent
-# ├── yolov5
-# └── datasets
-#     └── imagenet  ← downloads here
-
-# Arguments (optional) Usage: bash data/scripts/get_imagenet.sh --train --val
-if [ "$#" -gt 0 ]; then
-  for opt in "$@"; do
-    case "${opt}" in
-    --train) train=true ;;
-    --val) val=true ;;
-    esac
-  done
-else
-  train=true
-  val=true
-fi
-
-# Make dir
-d='../datasets/imagenet' # unzip directory
-mkdir -p $d && cd $d
-
-# Download/unzip train
-if [ "$train" == "true" ]; then
-  wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_train.tar # download 138G, 1281167 images
-  mkdir train && mv ILSVRC2012_img_train.tar train/ && cd train
-  tar -xf ILSVRC2012_img_train.tar && rm -f ILSVRC2012_img_train.tar
-  find . -name "*.tar" | while read NAME; do
-    mkdir -p "${NAME%.tar}"
-    tar -xf "${NAME}" -C "${NAME%.tar}"
-    rm -f "${NAME}"
-  done
-  cd ..
-fi
-
-# Download/unzip val
-if [ "$val" == "true" ]; then
-  wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_val.tar # download 6.3G, 50000 images
-  mkdir val && mv ILSVRC2012_img_val.tar val/ && cd val && tar -xf ILSVRC2012_img_val.tar
-  wget -qO- https://raw.githubusercontent.com/soumith/imagenetloader.torch/master/valprep.sh | bash # move into subdirs
-fi
-
-# Delete corrupted image (optional: PNG under JPEG name that may cause dataloaders to fail)
-# rm train/n04266014/n04266014_10835.JPEG
-
-# TFRecords (optional)
-# wget https://raw.githubusercontent.com/tensorflow/models/master/research/slim/datasets/imagenet_lsvrc_2015_synsets.txt