You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
53 lines
1.5 KiB
53 lines
1.5 KiB
2 years ago
|
import requests
|
||
|
|
from cv2 import cv2
|
||
|
|
import numpy as np
|
||
|
|
import json
|
||
|
|
import os
|
||
|
|
|
||
|
|
from datetime import datetime
|
||
|
|
|
||
|
|
|
||
|
|
API_URL = 'http://127.0.0.1:8000'
|
||
|
|
|
||
|
|
img_dir = '../../usable_imgs/'
|
||
|
|
|
||
|
|
cv2.namedWindow('Input Image')
|
||
|
|
cv2.namedWindow('Predicted Disparity')
|
||
|
|
|
||
|
|
|
||
|
|
def normalize_and_colormap(img):
|
||
|
|
ret = (img - img.min()) / (img.max() - img.min()) * 255.0
|
||
|
|
ret = ret.astype("uint8")
|
||
|
|
ret = cv2.applyColorMap(ret, cv2.COLORMAP_INFERNO)
|
||
|
|
return ret
|
||
|
|
|
||
|
|
|
||
|
|
for img in os.scandir(img_dir):
|
||
|
|
if 'ir' not in img.path:
|
||
|
|
continue
|
||
|
|
input_img = cv2.imread(img.path)
|
||
|
|
if input_img.shape == (1024, 1280, 3):
|
||
|
|
diff = (512 - 480) // 2
|
||
|
|
downsampled = cv2.pyrDown(input_img)
|
||
|
|
input_img = downsampled[diff:downsampled.shape[0]-diff, 0:downsampled.shape[1]]
|
||
|
|
|
||
|
|
openBin = {'file': ('file', open(img.path, 'rb'), 'image/png')}
|
||
|
|
|
||
|
|
print('sending image')
|
||
|
|
start = datetime.now()
|
||
|
|
r = requests.put(f'{API_URL}/ir', files=openBin)
|
||
|
|
end = datetime.now()
|
||
|
|
print('received response')
|
||
|
|
print(f'processing took {end - start}')
|
||
|
|
r.raise_for_status()
|
||
|
|
|
||
|
|
# FIXME yuck, don't json the json
|
||
|
|
pred_disp = np.asarray(json.loads(json.loads(r.text))['disp'], dtype='uint8')
|
||
|
|
ref_pat = np.asarray(json.loads(json.loads(r.text))['reference'], dtype='uint8').transpose((2,0,1)).astype('uint8')
|
||
|
|
pred_disp = cv2.transpose(pred_disp)
|
||
|
|
|
||
|
|
cv2.imshow('Input Image', input_img)
|
||
|
|
# cv2.imshow('Reference Image', ref_pat)
|
||
|
|
cv2.imshow('Predicted Disparity', normalize_and_colormap(pred_disp))
|
||
|
|
cv2.waitKey()
|