Esempi in Python per PANDA_IMAGE

Esempio n. 1

File: yzydemo.py Progetto: JoanYu/PANDA-Toolkit

def main():
    image_root = '/Users/xduyzy/Downloads/PANDA_IMAGE'
    person_anno_file = 'person_bbox_train.json'
    annomode = 'person'
    example = PANDA_IMAGE(image_root,
                          person_anno_file,
                          annomode='person',
                          showwidth=1280)
    # example.showImgs(range=1)
    # print('starting save images with annos...')
    example.showAnns(range=5, shuffle=True, saveimg=True)

Esempio n. 2

File: split_image.py Progetto: worry74147/detection_toolkits

def main(args):

    image_root = args.data_dir
    anno_path = args.groudtruth_path
    anno_mode = args.anno_mode
    output_dir = args.output_dir
    output_anno_path = os.path.join(output_dir, 'split.json')

    os.makedirs(output_dir, exist_ok=True)

    example = PANDA_IMAGE(image_root, anno_path, annomode=anno_mode)

    splitter = ImgSplit(image_root, anno_path, anno_mode, output_dir, output_anno_path)

    splitter.splitdata(0.5)

    print('Done.')

Esempio n. 3

File: split_single_image.py Progetto: worry74147/detection_toolkits

def main(args):

    image_root = args.image_dir
    image_name = args.image_name
    anno_path = args.groudtruth_path
    anno_mode = args.anno_mode
    output_dir = args.output_dir

    output_anno_path = os.path.join(output_dir, 'split_coco.json')

    os.makedirs(output_dir, exist_ok=True)

    example = PANDA_IMAGE(image_root, anno_path, annomode=anno_mode)

    splitter = ImgSplit(image_root, anno_path, anno_mode, output_dir, output_anno_path)

    patch_annos = splitter.SplitSingle(image_name, 0.25)

    print('Done.')

Esempio n. 4

File: demo.py Progetto: JoanYu/PANDA-Toolkit

# --------------------------------------------------------
# Tool kit function demonstration
# Written by Wang Xueyang ([email protected]), Version 20200321
# Inspired from DOTA dataset devkit (https://github.com/CAPTAIN-WHU/DOTA_devkit)
# --------------------------------------------------------

from PANDA import PANDA_IMAGE, PANDA_VIDEO
import panda_utils as util
from ImgSplit import ImgSplit
from ResultMerge import DetResMerge

if __name__ == '__main__':
    image_root = '/Users/xduyzy/Downloads/PANDA_IMAGE'
    person_anno_file = 'person_bbox_train.json'
    annomode = 'person'
    example = PANDA_IMAGE(image_root, person_anno_file, annomode='person')
    '''1. show images'''
    # example.showImgs()
    '''2. show annotations'''
    # example.showAnns(range=50, shuffle=True)
    '''
    3. Split Image And Label
    We provide the scale param before split the images and labels.
    '''
    # outpath = 'split'
    # outannofile = 'split.json'
    # split = ImgSplit(image_root, person_anno_file, annomode, outpath, outannofile)
    # split.splitdata(0.5)
    '''
    4. Merge patches
    Now, we will merge these patches to see if they can be restored in the initial large images

Esempio n. 5

# --------------------------------------------------------
# Tool kit function demonstration
# Written by Wang Xueyang ([email protected]), Version 20200321
# Inspired from DOTA dataset devkit (https://github.com/CAPTAIN-WHU/DOTA_devkit)
# --------------------------------------------------------

from PANDA import PANDA_IMAGE, PANDA_VIDEO
import panda_utils as util
from ImgSplit import ImgSplit
from ResultMerge import DetResMerge

if __name__ == '__main__':
    image_root = 'G:/PANDA/PANDA_IMAGE'
    person_anno_file = 'human_bbox_train.json'
    annomode = 'person'
    example = PANDA_IMAGE(image_root, person_anno_file, annomode='person')

    '''1. show images'''
    example.showImgs()

    '''2. show annotations'''
    example.showAnns(range=50, shuffle=True)

    '''
    3. Split Image And Label
    We provide the scale param before split the images and labels.
    '''
    outpath = 'split'
    outannofile = 'split.json'
    split = ImgSplit(image_root, person_anno_file, annomode, outpath, outannofile)
    split.splitdata(0.5)

Esempio n. 6

File: demo_show_anno.py Progetto: tranorrepository/gigavision

# split.splitdata(0.5)

# person_anno_file =r"person_s0.5_t0.9_train_02_split.json"
# basepath=r'/root/data/gvision/all-obj-split/center'#主目录
# person_anno_file =r"pv_split_obj.json"
# vehicle_anno_file = 'pv_split_obj.json'
# annomode='headbbox'
# annomode='person'
# example = PANDA_IMAGE(basepath, person_anno_file, annomode,addmode="image_train",savepath="my_annos_in_image_p" )
# 'person', 'vehicle', 'person&vehicle', 'headbbox' or 'headpoint'
annomode = 'crowd'
person_anno_file = r"person_bbox_train.json"
basepath = r'/root/data/gvision/dataset/raw_data'  #主目录
vehicle_anno_file = 'vehicle_bbox_train.json'

example = PANDA_IMAGE(basepath,
                      person_anno_file,
                      annomode=annomode,
                      addmode="image_train",
                      savepath="annos_in_image_crowd",
                      showcate=False)
# # # '''1. show images'''vehicle
# # # example.showImgs(range=2)

# # '''2. show annotations'''"01_University_Canteen/IMG_01_02.jpg""10_Ceremony/IMG_10_21.jpg"
example.showAnns(imgrequest=None,
                 range=1,
                 imgfilters=["10_Ceremony/IMG_10_21.jpg"],
                 shuffle=True,
                 saveimg=True)