pose2sim/Pose2Sim/Utilities/json_display_without_img.py

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
#####################################################
## Display json 2d detections on an animated graph ##
#####################################################
This tool lets you display 2D coordinates json files on an animated graph.
High confidence keypoints are green, low confidence ones are red.
Note: See 'json_display_without_img.py' if you want to overlay the json
coordinates on the original images.
Usage:
python -m json_display_without_img -j json_folder -W 1920 -H 1080
python -m json_display_without_img -j json_folder -o output_img_folder -d True -s True -W 1920 -H 1080 - 30
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import json_display_without_img; json_display_without_img.json_display_without_img_func(json_folder=r'<json_folder>', image_width=1920, image_height = 1080)
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'''
## INIT
import os
import numpy as np
import json
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation, FileMovieWriter
import argparse
## AUTHORSHIP INFORMATION
__author__ = "David Pagnon"
__copyright__ = "Copyright 2021, Pose2Sim"
__credits__ = ["David Pagnon"]
__license__ = "BSD 3-Clause License"
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__version__ = '0.6'
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__maintainer__ = "David Pagnon"
__email__ = "contact@david-pagnon.com"
__status__ = "Development"
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## FUNCTIONS
def save_inp_as_output(_img, c_name, dpi=100):
h, w, _ = _img.shape
fig, axes = plt.subplots(figsize=(h/dpi, w/dpi))
fig.subplots_adjust(top=1.0, bottom=0, right=1.0, left=0, hspace=0, wspace=0)
axes.imshow(_img)
axes.axis('off')
plt.savefig(c_name, dpi=dpi, format='jpeg')
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def json_display_without_img_func(**args):
'''
This function lets you display 2D coordinates json files on an animated graph.
High confidence keypoints are green, low confidence ones are red.
Note: See 'json_display_without_img.py' if you want to overlay the json
coordinates on the original images.
Usage:
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json_display_without_img -j json_folder -W 1920 -H 1080
json_display_without_img -j json_folder -o output_img_folder -d True -s True -W 1920 -H 1080
import json_display_without_img; json_display_without_img.json_display_without_img_func(json_folder=r'<json_folder>', image_width=1920, image_height = 1080)
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'''
json_folder = os.path.realpath(args.get('json_folder'))
json_fnames = [f for f in os.listdir(json_folder) if os.path.isfile(os.path.join(json_folder, f))]
json_fnames.sort(key=lambda f: int(f.split('_')[0])) # sort by frame number
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output_img_folder = args.get('output_img_folder')
if output_img_folder==None:
output_img_folder = os.path.join(json_folder+'_img')
else:
output_img_folder = os.path.realpath(output_img_folder)
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image_width = args.get('image_width')
if image_width==None:
image_width = 2000
else:
image_width = int(image_width)
image_height = args.get('image_height')
if image_height==None:
image_height = 2000
else:
image_height = int(image_height)
frame_rate = int(args.get('frame_rate'))
if frame_rate==None:
frame_rate = 30
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display = args.get('display')
if display==None:
display = True
save = args.get('save')
# Save
if save == True or save == 'True':
if not os.path.exists(output_img_folder):
os.mkdir(output_img_folder)
# Données json
X,Y,CONF = [], [], []
for json_fname in json_fnames:
xfrm, yfrm, conffrm = np.array([]), np.array([]), np.array([]) # Coordinates of all people in frame
with open(os.path.join(json_folder,json_fname)) as json_f:
json_file = json.load(json_f)
for ppl in range(len(json_file['people'])):
keypt = np.asarray(json_file['people'][ppl]['pose_keypoints_2d']).reshape(-1,3)
xfrm = np.concatenate((xfrm,keypt[:,0]))
yfrm = np.concatenate((yfrm,keypt[:,1]))
conffrm = np.concatenate((conffrm,keypt[:,2]))
X += [xfrm]
Y += [yfrm]
CONF += [conffrm]
# Scatterplot
def update(frame):
if frame==len(json_fnames)-1:
plt.close(fig)
else:
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scat.set_offsets(np.c_[X[frame], image_height-Y[frame]])
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scat.set_array(CONF[frame])
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if save == True or save=='True' or save == '1':
output_name = os.path.join(output_img_folder, f'{os.path.basename(output_img_folder)}_{str(frame).zfill(5)}.png')
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plt.savefig(output_name)
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return scat,
fig = plt.figure()
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ax = plt.axes(xlim = (0,image_width), ylim = (0,image_height))
ax.set_aspect('equal', adjustable='box')
scat = ax.scatter(X[0],image_height-Y[0], marker='+', cmap='RdYlGn', c=CONF[0])
interval_img = int(1000/frame_rate)
anim = FuncAnimation(fig, update, interval=interval_img, frames=np.arange(len(json_fnames)), repeat=False) #, blit=True
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# Display
if display == True or display == 'True' or display =='1':
plt.show()
plt.close('all')
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if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-j', '--json_folder', required = True, help='folder of json 2D coordinate files')
parser.add_argument('-W', '--image_width', required = False, help='image width')
parser.add_argument('-H', '--image_height', required = False, help='image height')
parser.add_argument('-f', '--frame_rate', required = False, help='frame rate')
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parser.add_argument('-o', '--output_img_folder', required=False, help='custom folder name for coordinates overlayed on images')
parser.add_argument('-d', '--display', default=True, required = False, help='display images with overlayed coordinates')
parser.add_argument('-s', '--save', default=False, required = False, help='save images with overlayed 2D coordinates')
args = vars(parser.parse_args())
json_display_without_img_func(**args)