I am trying to run a project from github , every object counter applications using sort algorithm. I can't run any of them because of a specific error, attaching errors screenshot. Can anyone help me about fixing this issue?
The linear_assignment function is deprecated in 0.21 and will be removed from 0.23, but sklearn.utils.linear_assignment_ can be replaced by scipy.optimize.linear_sum_assignment.
You can use:
from scipy.optimize import linear_sum_assignment as linear_assignment
then you can run the file and don't need to change the code.
pip install scikit-learn==0.22.2
As yiakwy points out in a github comment the scipy.optimize.linear_sum_assignment is not the perfect replacement:
I am concerned that linear_sum_assignment is not equivalent to linear_assignment which later implements "maximum values" matching strategy not "complete matching" strategy, i.e. in tracking problem maybe an old landmark lost and a new detection coming in. We don't have to make a complete assignment, just match as more as possible.
I have found this out while trying to use it inside SORT-based yolo tracking code which that replacement broke (I was lucky that it did otherwise, I would get wrong results from the experiments without realising it...)
Instead, I suggest copying the module itself to the last version of sklearn and include as module in your code.
https://github.com/scikit-learn/scikit-learn/blob/0.22.X/sklearn/utils/linear_assignment_.py
For instance if you copy this file into an utils directory import with from utils.linear_assignment_ import linear_assignment
Solution
Use pip to install lap and optionally scipy
Uncomment the import and use the following function
def linear_assignment(cost_matrix):
try:
import lap
_, x, y = lap.lapjv(cost_matrix, extend_cost=True)
return np.array([[y[i], i] for i in x if i >= 0])
except ImportError:
from scipy.optimize import linear_sum_assignment
x, y = linear_sum_assignment(cost_matrix)
return np.array(list(zip(x, y)))
You are getting this error because you haven't install scikit module yet.
Install scikit-learn module from https://pypi.org/project/scikit-learn/
Related
I am trying to take advantage of the pysrim package to run some batch simulations of SRIM/TRIM in Jupyter notebook. I was able to successful install both the program and the package but am getting an error "TypeError: load() missing 1 required positional argument: 'Loader'" when using pysrim. Initially I assumed my Python version was to up to date (3.9.12) but am still getting this issue even after setting up a 3.6 environment. I understand this is a most likely a pretty niche question but any help would be much appreciated. Code pasted below.
import os
import numpy as np
import matplotlib.pyplot as plt
from srim import TRIM, Ion, Layer, Target
from srim.output import Results
Thanks!
Okay looks like I needed to change a small part of the program. I first navigated to C:\Users\<username>\Anaconda3\Lib\site-packages\srim\core and opened the file elementsdb.py. On line 10 I changed return yaml.load(open(dbpath, "r")) to
return yaml.full_load(open(dbpath, "r")) and the issue was resolved.
I want to replicate the code here, and I get the following error while running in Google Colab?
ImportError: cannot import name 'zero_gradients' from
'torch.autograd.gradcheck'
(/usr/local/lib/python3.7/dist-packages/torch/autograd/gradcheck.py)
Can someone help me with how to solve this?
This seems like it's using a very old version of PyTorch, the function itself is not available anymore. However, if you look at this commit, you will see the implementation of zero_gradients. What it does is simply zero out the gradient of the input:
def zero_gradients(i):
for t in iter_gradients(i):
t.zero_()
Then zero_gradients(x) should be the same as x.zero_grad(), which is the current API, assuming x is a nn.Module!
Or it's just:
if x.grad is not None:
x.grad.zero_()
I'm trying to examine multiple tone-mapping operators in Open CV, using Python.
Various sources use four operators (Drago, Durand, Reinhard, Mantiuk). Three of them work. However, when I call up cv2.createTonemapDurand(), I get this error:
AttributeError: module 'cv2.cv2' has no attribute 'createTonemapDurand'
Is it possible to call the Durand operator somehow, or did Open CV drop that one recently?
Thanks!
I'll switch from comment to answer to have a better representation.
you just have to :
import cv2
cv2.xphoto.createTonemapDurand()
Be aware that, if u compiled opencv by yourself, you had to check OPENCV_ENABLE_NONFREE.
Please post your code where you import cv2 and call the function. If you want to look for some functions, attributes or whatever either look in the documentation of the package or use dir() and type(). For your example you can use this:
import cv2
from re import match
cv2_filtered = filter(lambda v: match('.*Tonemap', v), dir(cv2))
[print(val) for val in cv2_filtered]
Returns:
Tonemap
TonemapDrago
TonemapMantiuk
TonemapReinhard
createTonemap
createTonemapDrago
createTonemapMantiuk
createTonemapReinhard
Seems like there is no function createTonemapDurand in cv2.
I'm currently using a python module called petsc4py (https://pypi.org/project/petsc4py/). My main issue is that none of the typical intellisense features seems to work with this module.
I'm guessing it might have something to do with it being a C extension module, but I am not sure exactly why this happens. I initially thought that intellisense was unable to look inside ".so" files, but it seems that numpy is able to do this with the array object, which in my case is inside a file called multiarray.cpython-37m-x86_64-linux-gnu (check example below).
Does anyone know why I see this behaviour in the petsc4py module. Is there anything that I (or the developers of petsc4py) can do to get intellisense to work?
Example:
import sys
import petsc4py
petsc4py.init(sys.argv)
from petsc4py import PETSc
x_p = PETSc.Vec().create()
x_p.setSizes(10)
x_p.setFromOptions()
u_p = x_p.duplicate()
import numpy as np
x_n = np.array([1,2,3])
u_n = x_n.copy()
In this example, when trying to work with a Vec object from petsc4py, doing u_p.duplicate() cannot find the function and the suggestion is simply a repetition of the function immediately before. However, using an array from numpy, doing u_n.copy() works perfectly.
If you're compiling in-place then you're bumping up against https://github.com/microsoft/python-language-server/issues/197.
When attempting to pass my RNN call, I call tf.nn.rnn_cell and I receive the following error:
AttributeError: module 'tensorflow.python.ops.nn' has no attribute 'rnn_cell'
Which is odd, because I'm sure I imported everything correctly:
from __future__ import print_function, division
from tensorflow.contrib import rnn
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
But looking at the docs, things have moved around between tensorflow versions.
what would you all recommend to fix this??
Line, I'm getting the error against:
state_per_layer_list = tf.unstack(init_state, axis=0)
rnn_tuple_state = tuple(
[tf.nn.rnn_cell.LSTMStateTuple(state_per_layer_list[idx][0], state_per_layer_list[idx][1])
for idx in range(num_layers)]
)
Specifically:
tf.nn.rnn_cell
I'm using anaconda 3 to manage all of this so, the dependancies should all be taken care of. I have already tried working around a damn rank/shape error with Tensor shapes which took ages to resolve.
Cheers in advance.
Replace tf.nn.rnn_cell with tf.contrib.rnn
Since version 1.0, rnn implemented as part of the contrib module.
More information can be found here
https://www.tensorflow.org/api_guides/python/contrib.rnn