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Firstly, let me commend you on your effort for this paper and the repo that accompanies it. As a programmer myself, I know how difficult it is to write code especially for machine learning models.
I successfully, reproduced the results through a GPU hardware and the code code ran up until:
Besides, I also had to downgrade SCIPY to 1:00 because of the depreciated imgresize issue.
/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:108: DeprecationWarning: imresizeis deprecated!imresizeis deprecated in SciPy 1.0.0, and will be removed in 1.2.0. Use ``skimage.transform.resize`` instead. /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:104: DeprecationWarning:imresizeis deprecated!imresize is deprecated in SciPy 1.0.0, and will be removed in 1.2.0. Use ``skimage.transform.resize`` instead.
perhaps you could look into these issues.
Additionally, running:
`# Prepare liver patch for step2
net1 output is used to determine the predicted liver bounding box
Firstly, let me commend you on your effort for this paper and the repo that accompanies it. As a programmer myself, I know how difficult it is to write code especially for machine learning models.
I successfully, reproduced the results through a GPU hardware and the code code ran up until:
# Visualize results imshow(img_p, lbl_p, pred>0.5, title=['Slice','Ground truth', 'Prediction'])
Besides, I also had to downgrade SCIPY to 1:00 because of the depreciated imgresize issue.
/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:108: DeprecationWarning:
imresizeis deprecated!
imresizeis deprecated in SciPy 1.0.0, and will be removed in 1.2.0. Use ``skimage.transform.resize`` instead. /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:104: DeprecationWarning:
imresizeis deprecated!
imresizeis deprecated in SciPy 1.0.0, and will be removed in 1.2.0. Use ``skimage.transform.resize`` instead.
perhaps you could look into these issues.
Additionally, running:
`# Prepare liver patch for step2
net1 output is used to determine the predicted liver bounding box
img_p2, bbox = step2_preprocess_img_slice(img_p, pred)
imshow(img_p2)`
gave the following error:
`---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
in ()
----> 1 img_p2, bbox = step2_preprocess_img_slice(img_p, pred)
2 imshow(img_p2)
in step2_preprocess_img_slice(img_p, step1_pred)
79 y2 = min(img.shape[0], y2+y_pad)
80
---> 81 img = img[y1:y2+1, x1:x2+1]
82 pred = pred[y1:y2+1, x1:x2+1]
83
TypeError: slice indices must be integers or None or have an index method`
these affected the rest of the executions such as:
extract liver portion as predicted by net1
x1,x2,y1,y2 = bbox
lbl_p_liver = lbl_p[y1:y2,x1:x2]
Set labels to 0 and 1
lbl_p_liver[lbl_p_liver==1]=0
lbl_p_liver[lbl_p_liver==2]=1
imshow(img_p2[92:-92,92:-92],lbl_p_liver, pred2>0.5)`
# Load step2 network net2 = caffe.Net(STEP2_DEPLOY_PROTOTXT, STEP2_MODEL_WEIGHTS, caffe.TEST)
and finally
net2.blobs['data'].data[0,0,...] = img_p2 pred2 = net2.forward()['prob'][0,1] print (pred2.shape)
Please could you kindly proffer solutions to these issues?
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