Cpt.Captain/CREStereo-pytorch-nxt
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frontend/__init__.py: general improvements

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This commit is contained in:
Nils Koch 2022-06-02 15:03:38 +02:00
parent 50581efa01
commit 922bd3ab80
1 changed files with 33 additions and 28 deletions
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61
frontend/__init__.py
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@ -32,20 +32,23 @@ def normalize_and_colormap(img):
def change_epoch(): def change_epoch():
global r
epoch = input('Enter epoch number or "latest"\n') epoch = input('Enter epoch number or "latest"\n')
r = requests.post(f'{API_URL}/model/update/{epoch}') r = requests.post(f'{API_URL}/model/update/{epoch}')
print(r.text) print(r.text)
def extract_data(r): def extract_data(data):
# FIXME yuck, don't json the json # FIXME yuck, don't json the json
data = json.loads(json.loads(r.text)) duration = data['duration']
pred_disp = np.asarray(data['disp'], dtype='uint8')
# get result and rotate 90 deg
pred_disp = cv2.transpose(np.asarray(data['disp'], dtype='uint8'))
if input not in data:
return pred_disp, duration
in_img = np.asarray(data['input'], dtype='uint8').transpose((2, 0, 1)) in_img = np.asarray(data['input'], dtype='uint8').transpose((2, 0, 1))
ref_pat = np.asarray(data['reference'], dtype='uint8').transpose((2, 0, 1)) ref_pat = np.asarray(data['reference'], dtype='uint8').transpose((2, 0, 1))
duration = data['duration']
pred_disp = cv2.transpose(pred_disp)
return pred_disp, in_img, ref_pat, duration return pred_disp, in_img, ref_pat, duration
@ -65,32 +68,34 @@ def put_image(img_path):
r = requests.put(f'{API_URL}/ir', files=openBin) r = requests.put(f'{API_URL}/ir', files=openBin)
print('received response') print('received response')
r.raise_for_status() r.raise_for_status()
return r data = json.loads(json.loads(r.text))
return data
while True: if __name__ == '__main__':
for img in os.scandir(img_dir): while True:
start = datetime.now() for img in os.scandir(img_dir):
if 'ir' not in img.path: start = datetime.now()
continue if 'ir' not in img.path:
continue
# alternatively: use img.path for native size # alternatively: use img.path for native size
downsize_input_img() downsize_input_img()
r = put_image('buffer.png') data = put_image('buffer.png')
pred_disp, in_img, ref_pat, duration = extract_data(r) pred_disp, in_img, ref_pat, duration = extract_data(data)
print(f'inference took {duration:1.4f}s') print(f'inference took {duration:1.4f}s')
print(f'pipeline and transfer took another {(datetime.now() - start).total_seconds() - float(duration):1.4f}s') print(f'pipeline and transfer took another {(datetime.now() - start).total_seconds() - float(duration):1.4f}s')
print(f"Pred. Disparity: \n\t{pred_disp.min():.{2}f}/{pred_disp.max():.{2}f}\n") print(f"Pred. Disparity: \n\t{pred_disp.min():.{2}f}/{pred_disp.max():.{2}f}\n")
cv2.imshow('Input Image', in_img) cv2.imshow('Input Image', in_img)
# cv2.imshow('Reference Image', ref_pat) # cv2.imshow('Reference Image', ref_pat)
cv2.imshow('Normalized Predicted Disparity', normalize_and_colormap(pred_disp)) cv2.imshow('Normalized Predicted Disparity', normalize_and_colormap(pred_disp))
cv2.imshow('Predicted Disparity', pred_disp) cv2.imshow('Predicted Disparity', pred_disp)
key = cv2.waitKey() key = cv2.waitKey()
if key == 113: if key == 113:
quit() quit()
elif key == 101: elif key == 101:
change_epoch() change_epoch()