如果您想了解类型错误：'numpy.float32'对象不可调用的相关知识，那么本文是一篇不可错过的文章，我们将对python中对象不可调用进行全面详尽的解释，并且为您提供关于'AttributeEr
如果您想了解类型错误：'numpy.float32' 对象不可调用的相关知识，那么本文是一篇不可错过的文章，我们将对python中对象不可调用进行全面详尽的解释，并且为您提供关于'AttributeError：'numpy.float32'对象没有属性'ctypes'、DJANGO：类型错误“需要一个整数”并且类型错误“bool”对象不可调用、Julia Flux 错误：MethodError：没有方法匹配 *(::Chain{Tuple{Conv{2,4,typeof(identity),Array{Float32,4},Array{Float32,1}},var"#13#15" }}, ::Int64)、numpy – 在pandas 0.10.1上使用pandas.read_csv指定dtype float32的有价值的信息。
本文目录一览：- 类型错误：'numpy.float32' 对象不可调用（python中对象不可调用）
- 'AttributeError：'numpy.float32'对象没有属性'ctypes'
- DJANGO：类型错误“需要一个整数”并且类型错误“bool”对象不可调用
- Julia Flux 错误：MethodError：没有方法匹配 *(::Chain{Tuple{Conv{2,4,typeof(identity),Array{Float32,4},Array{Float32,1}},var"#13#15" }}, ::Int64)
- numpy – 在pandas 0.10.1上使用pandas.read_csv指定dtype float32
类型错误：'numpy.float32' 对象不可调用（python中对象不可调用）
如何解决类型错误：''numpy.float32'' 对象不可调用
我不明白为什么我会收到这个错误。谁能帮我吗？我是 python 的初学者，这个错误困扰着我。该函数基本上用于连接组件标记，但我发现使用 python 的 max() 函数很难获得最大值，如下所示。
一定是我遗漏了一些小错误。任何形式的帮助将不胜感激。
import cv2
import numpy as np
import matplotlib.pyplot as plt
from skimage.morphology import disk
%matplotlib inline
def ccl(img):
##### first pass #####
curr_label = 1;
img = np.array(img)
labels = np.array(img)
# storing label conversions
label_conv = []
label_conv.append([])
label_conv.append([])
count = 0
for i in range(1,len(img)):
for j in range(1,len(img[0])):
if img[i][j] > 0:
label_x = int(labels[i][j - 1])
label_y = int(labels[i - 1][j])
if label_x > 0:
# both x and y have a label
if label_y > 0:
if not label_x == label_y:
labels[i][j] = min(label_x,label_y)
#print("i: ",i,"j: ",j)
#print("label_x: ",type(label_x),"label_y: ",type(label_y))
max_label = max(label_x,label_y)
if max_label not in label_conv[0]:
label_conv[0].append(max(label_x,label_y))
label_conv[1].append(min(label_x,label_y))
elif max(label_x,label_y) in label_conv[0]:
ind = label_conv[0].index(max(label_x,label_y))
if label_conv[1][ind] > min(label_x,label_y):
l = label_conv[1][ind]
label_conv[1][ind] = min(label_x,label_y)
while l in label_conv[0] and count < 100:
count += 1
ind = label_conv[0].index(l)
l = label_conv[1][ind]
label_conv[1][ind] = min(label_x,label_y)
label_conv[0].append(l)
label_conv[1].append(min(label_x,label_y))
else:
labels[i][j] = label_y
# only x has a label
else:
labels[i][j] = label_x
# only y has a label
elif label_y > 0:
labels[i][j] = label_y
# neither x nor y has a label
else:
labels[i][j] = curr_label
curr_label += 1
##### second pass #####
count = 1
for idx,val in enumerate(label_conv[0]):
if label_conv[1][idx] in label_conv[0] and count < 100:
count += 1
ind = label_conv[0].index(label_conv[1][idx])
label_conv[1][idx] = label_conv[1][ind]
for i in range(1,len(labels)):
for j in range(1,len(labels[0])):
if labels[i][j] in label_conv[0]:
ind = label_conv[0].index(labels[i][j])
labels[i][j] = label_conv[1][ind]
return labels
img = cv2.imread("..\\\\disks.png",0)
img2 = cv2.bitwise_not(img,mask = None)
SE = disk(25)
img_eroded = cv2.erode(img2,SE) #Erode the image
plt.figure(figsize=(16,12))
plt.subplot(1,1,1)
plt.imshow(img_eroded,cmap="gray")
plt.title(''Image'')
plt.xticks([])
plt.yticks([])
labels = ccl(img_eroded)
print("size: ",labels)
plt.figure(figsize=(16,cmap="gray")
plt.title(''Image'')
plt.xticks([])
plt.yticks([])
这是我得到的错误输出。
TypeError Traceback (most recent call last)
<ipython-input-83-04f5b3d4d1e5> in <module>
103 plt.yticks([])
104
--> 105 labels = ccl(img_eroded)
106
107 print("size: ",labels)
<ipython-input-83-04f5b3d4d1e5> in ccl(img)
34 #print("i: ",j)
35 #print("label_x: ",type(label_y))
---> 36 max_label = max(label_x,label_y)
37
38 if max_label not in label_conv[0]:
TypeError: ''numpy.float32'' object is not callable
enter code here
解决方法
这看起来您之前已将 max 指定为指向 numpy int 的变量。然后，当您尝试调用 max() 函数时，它会尝试调用您创建的变量。
清除命名空间，然后再次运行。
'AttributeError：'numpy.float32'对象没有属性'ctypes'
如何解决''AttributeError：''numpy.float32''对象没有属性''ctypes''
我试图根据从左上，右上等顺序排列的点来计算图像的尺寸。因此，我以后可以执行4点透视变换和变形。 （使用opencvSharp和numpy.net）
我想从中获取最大宽度和最大高度作为整数 ndarray，但此时它抛出 “ Python.Runtime.PythonException：''AttributeError：''numpy.float32''对象没有属性''ctypes''
不太确定如何作为一个新手来解决这个问题，这是我第一次使用此OpencvSharp和numpy.NET。
ndarray rect = OrderPoints(pts);
// 4 Points order from top-left top- right etc..
ndarray tL = rect[0],tR = rect[1],bR = rect[2],bL = rect[3];
// width of new image
ndarray w1 = ((bR[0] - bL[0]) * (bR[0] - bL[0])) + ((bR[1] - bL[1]) * (bR[1] - bL[1])); // quietly throws exception here
ndarray w2 = ((tR[0] - tL[0]) * (tR[0] - tL[0])) + ((tR[1] - tL[1]) * (tR[1] - tL[1]));
w1 = np.sqrt(w1);
w2 = np.sqrt(w2);
// get max width as an interger
int[] width1 = w1.GetData<int>(); // same error blows up here
int[] width2 = w2.GetData<int>();
int maxWidth = Math.Max(width1[0],width2[0]);
ndarray h1 = ((tR[0] - bR[0]) * (tR[0] - bR[0])) + ((tR[1] - bR[1]) * (tR[1] - bR[1]));
ndarray h2 = (tL[0] - bL[0]) * (tL[0] - bL[0]) + (tL[1] - bL[1]) * (tL[1] - bL[1]);
h1 = np.sqrt(h1);
h2 = np.sqrt(h2);
int[] height = h1.GetData<int>();
int[] height2 = h2.GetData<int>();
int maxHeight = Math.Max(height[0],height2[0]);
// make a top - down view
var dst = np.array(
new[,] {
{ 0,0},{maxWidth - 1,0 },maxHeight - 1 },{0,maxHeight - 1 }
});
var rectPts = rect.GetData<Point2f>();
var dstarray = dst.GetData<Point2f>();
Mat matr = Cv2.GetPerspectiveTransform(rectPts,dstarray);
Mat output = new Mat();
Cv2.WarpPerspective(image,output,matr,new Size(maxWidth,maxHeight));
return output;
解决方法
我设法提出了一个解决方案，方法是使用repr属性返回数据字符串，然后将其解析为float并转换为Int。
int width1 = (int)float.Parse(w1.repr);
int width2 = (int)float.Parse(w2.repr);
DJANGO：类型错误“需要一个整数”并且类型错误“bool”对象不可调用
如何解决DJANGO：类型错误“需要一个整数”并且类型错误“bool”对象不可调用
我是 DJANGO 的新手，编码经验有限。
我正在学习一个涉及构建购物车的 DJANGO 教程。我收到：前端需要一个类型错误整数；以及当我尝试手动创建购物车时，管理门户中不可调用的类型错误 bool 对象。
我认为教程中的代码有点过时，但我有限的经验意味着我尝试的任何更改都会导致更多错误。
代码如下： #追溯
import pandas as pd
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
import numpy as np
import matplotlib as mpl
# Set plotting style
plt.style.use(''seaborn-white'')
dz=[]
z0 = np.array([ 1.,3.,11.,8.,7.,6.,5.,4.,10.,1.,])
dz.append(z0)
z1 =[ 5.,2.,0.,]
dz.append(z1)
z2 =[ 15.,]
dz.append(z2)
_zpos = z0*0
xlabels = pd.Index([''X01'',''X02'',''X03'',''X04''],dtype=''object'')
ylabels = pd.Index([''Y01'',''Y02'',''Y03'',''Y04'',''Y05'',''Y06'',''Y07''],dtype=''object'')
x = np.arange(xlabels.shape[0])
y = np.arange(ylabels.shape[0])
x_M,y_M = np.meshgrid(x,y,copy=False)
fig = plt.figure(figsize=(7,7))
ax = fig.add_subplot(111,projection=''3d'')
ax.set_Box_aspect((1,3.5,1))
plt.gca().view_init(15,20)
ls = mpl.colors.LightSource(azdeg=30,altdeg=10)
# Making the intervals in the axes match with their respective entries
ax.w_xaxis.set_ticks(x + 0.5/2.)
ax.w_yaxis.set_ticks(y + 0.5/2.)
# Renaming the ticks as they were before
ax.w_xaxis.set_ticklabels(xlabels)
ax.w_yaxis.set_ticklabels(ylabels)
# Labeling the 3 dimensions
ax.set_xlabel(''X label'')
ax.set_ylabel(''Y label'')
ax.set_zlabel(''Z label'')
# Choosing the range of values to be extended in the set colormap
values = np.linspace(0.2,x_M.ravel().shape[0])
# Selecting an appropriate colormap
colors = [''#FFC04C'',''blue'',''#3e9a19'',''#599be5'',''#bf666f'',''#a235bf'',''#848381'',''#fb90d6'',''#fb9125'']
# Increase the number of segment to 3 by changing the X in ''range(X)'' to 3.
for i in range(3):
ax.bar3d(x_M.ravel(),y_M.ravel(),_zpos,dx=0.2,dy=0.1,dz=dz[i],color=colors[i],lightsource=ls)
_zpos += dz[i]
Segment1_proxy = plt.Rectangle((0,0),1,fc="#FFC04C")
Segment2_proxy = plt.Rectangle((0,fc="blue")
Segment3_proxy = plt.Rectangle((0,fc="#3e9a19")
ax.legend([Segment1_proxy,Segment2_proxy,Segment3_proxy],[''Segment1'',''Segment2'',''Segment3''
])
plt.show()
settings.py
Internal Server Error: /cart/cart/
Traceback (most recent call last):
File "C:\\Users\\nia\\Desktop\\Pharma-mart\\env\\lib\\site-packages\\django\\core\\handlers\\exception.py",line 47,in inner
response = get_response(request)
File "C:\\Users\\nia\\Desktop\\Pharma-mart\\env\\lib\\site-packages\\django\\core\\handlers\\base.py",line 181,in _get_response
response = wrapped_callback(request,*callback_args,**callback_kwargs)
File "C:\\Users\\nia\\Desktop\\Pharma-mart\\pharmamart\\cart\\views.py",line 13,in cart_home
cart_obj = cart.objects.new_or_get(request)
File "C:\\Users\\nia\\Desktop\\Pharma-mart\\pharmamart\\cart\\models.py",line 11,in new_or_get
qs = self.getqueryset().filter(id=cart_id)
AttributeError: ''CartManager'' object has no attribute ''getqueryset''
[27/Mar/2021 10:49:42] "GET /cart/cart/ HTTP/1.1" 500 71680
#cart/admin.py
import os
from pathlib import Path
BASE_DIR = Path(__file__).resolve().parent.parent
SECRET_KEY =
DEBUG = True
ALLOWED_HOSTS = []
# Application deFinition
INSTALLED_APPS = [
''django.contrib.admin'',''django.contrib.auth'',''django.contrib.contenttypes'',''django.contrib.sessions'',''django.contrib.messages'',''django.contrib.staticfiles'',''store'',''patients'',''ckeditor'',''cart'',]
MIDDLEWARE = [
''django.middleware.security.SecurityMiddleware'',''django.contrib.sessions.middleware.SessionMiddleware'',''django.middleware.common.CommonMiddleware'',''django.middleware.csrf.CsrfViewMiddleware'',''django.contrib.auth.middleware.AuthenticationMiddleware'',''django.contrib.messages.middleware.MessageMiddleware'',''django.middleware.clickjacking.XFrameOptionsMiddleware'',]
ROOT_URLconf = ''pharmamart.urls''
TEMPLATES = [
{
''BACKEND'': ''django.template.backends.django.DjangoTemplates'',''Dirs'': [BASE_DIR / ''''],''APP_Dirs'': True,''OPTIONS'': {
''context_processors'': [
''django.template.context_processors.debug'',''django.template.context_processors.request'',''django.contrib.auth.context_processors.auth'',''django.contrib.messages.context_processors.messages'',],},]
Wsgi_APPLICATION = ''pharmamart.wsgi.application''
# Database
# https://docs.djangoproject.com/en/3.1/ref/settings/#databases
DATABASES = {
''default'': {
''ENGINE'': ''django.db.backends.sqlite3'',''NAME'': BASE_DIR / ''db.sqlite3'',}
}
# Password validation
# https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
''NAME'': ''django.contrib.auth.password_validation.UserAttributeSimilarityValidator'',{
''NAME'': ''django.contrib.auth.password_validation.MinimumLengthValidator'',{
''NAME'': ''django.contrib.auth.password_validation.CommonPasswordValidator'',{
''NAME'': ''django.contrib.auth.password_validation.NumericPasswordValidator'',]
# Internationalization
# https://docs.djangoproject.com/en/3.1/topics/i18n/
LANGUAGE_CODE = ''en-us''
TIME_ZONE = ''UTC''
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS,JavaScript,Images)
# https://docs.djangoproject.com/en/3.1/howto/static-files/
STATIC_URL = ''/static/''
MEDIA_URL =''/media/''
MEDIA_ROOT = os.path.join(BASE_DIR,''media'')
STATICFILES_Dirs = [
BASE_DIR / "static",]
LOGIN_REDIRECT_URL = ""
logoUT_REDIRECT_URL = ""
购物车/models.py
from django.contrib import admin
from .models import cart
admin.site.register(cart)
购物车/views.py
from django.db import models
from django.conf import settings
from store.models import product,customer
from django.contrib.auth.models import User
#User = settings.AUTH_USER.MODEL# if included it throws an error ''settings not defined''
class CartManager(models.Manager):
def new_or_get(self,request):
cart_id = request.session.get("cart_id",None)
qs = self.getqueryset().filter(id=cart_id)
if qs.count()==1:
new_obj = False
cart_obj = qs.first()
if request.user.is_authenticated() and cart_obj.user is None:
cart_obj-save()
else:
cart_obj = cart.objects.new(user=request.user)
new_obj = True
request.session[''cart_id''] = cart_obj.id
return cart_obj,new_obj
def new(self,user = None):
user_obj = None
if user is not None:
if user is authenticated():
user_obj = user
return self.model.objects.create(user=user_obj)
class cart(models.Model):
user = models.ForeignKey(User,related_name = "user",blank = True,null=True,on_delete=models.CASCADE)
product = models.ManyToManyField(''store.product'')
total = models.DecimalField(default = 0.0,max_digits = 50.00,decimal_places = 2)
updated = models.DateTimeField(auto_Now=True)
timestamp = models.DateTimeField(auto_Now=True)
objects = CartManager()
def __str__(self):
return str(self.id)
购物车/urls.py
from django.shortcuts import render
from django.contrib import admin
from django.contrib.auth.models import User
from .models import cart
# Create your views here.
#def cart_create(user=None):
# cart_obj = cart.objects.create(user = None)
# print(''New Cart created'')
# return cart_obj
def cart_home(request):
cart_obj = cart.objects.new_or_get(request)
return render(request,"home.html",{})
感谢任何有关修改代码以显示我的错误的帮助。
交流
Julia Flux 错误：MethodError：没有方法匹配 *(::Chain{Tuple{Conv{2,4,typeof(identity),Array{Float32,4},Array{Float32,1}},var"#13#15" }}, ::Int64)
如何解决Julia Flux 错误：MethodError：没有方法匹配 *(::Chain{Tuple{Conv{2,4,typeof(identity),Array{Float32,4},Array{Float32,1}},var"#13#15" }}, ::Int64)？
using Flux
using Flux:@functor
function ConvBlock(inc,out,k,s,p,use_act)
return Chain(
Conv((k,k),inc=>out,stride = s,pad = p,bias=true),use_act ? x -> leakyrelu.(x,0.2) : x -> x
)
end
mutable struct DenseResidualBlock
residual_beta
blocks
end
@functor DenseResidualBlock
function DenseResidualBlock(inc,c = 32,residual_beta = 0.2)
blocks = []
for i in 0:4
in_channels = inc + c*i
out_channels = i<=3 ? c : inc
use_act = i<=3 ? true : false
push!(blocks,ConvBlock(in_channels,out_channels,3,1,use_act))
end
return DenseResidualBlock(residual_beta,blocks)
end
function (m::DenseResidualBlock)(x)
new_inputs = x
local out,new_inputs
for block in m.blocks
out = block(new_inputs)
new_inputs = cat(new_inputs,dims=3)
end
return m.residual_beta * out + x
end
当我运行这个
drb = DenseResidualBlock(64)
我收到此错误 错误：方法错误：没有方法匹配 *(::Chain{Tuple{Conv{2,4,typeof(identity),Array{Float32,4},1}},var"#13#15"}},::Int64)
解决方法
试试
function DenseResidualBlock(inc;c = 32,residual_beta = 0.2)
代替
function DenseResidualBlock(inc,c = 32,residual_beta = 0.2)
当使用两个参数调用 DenseResidualBlock 时，您的代码中存在歧义。它可以直接构造 DenseResidualBlock 结构，也可以使用 DenseResidualBlock(inc,c) 调用 residual_beta = 0.2。如果您对 DenseResidualBlock(inc; c = 32,residual_beta = 0.2) 使用关键字参数，则会消除这种歧义。
错误消息表明，在 in_channels = inc + c*i 行，参数 c 不是预期的数字，而是无法乘以数字的 Flux.Chain。
numpy – 在pandas 0.10.1上使用pandas.read_csv指定dtype float32
我试图读一个简单的空间分隔的文件用pandas read_csv方法。然而，熊猫似乎没有服从我的dtype参数。也许我错误地指定它？
我已经把我对read_csv的一些复杂的调用归结为这个简单的测试用例。我实际上在我的“真实”场景中使用转换器的参数，但我删除了为简单。
下面是我的ipython会话：
>>> cat test.out
a b
0.76398 0.81394
0.32136 0.91063
>>> import pandas
>>> import numpy
>>> x = pandas.read_csv('test.out',dtype={'a': numpy.float32},delim_whitespace=True)
>>> x
a b
0 0.76398 0.81394
1 0.32136 0.91063
>>> x.a.dtype
dtype('float64')
我也试过这个用numpy.int32或numpy.int64的dtype。这些选择导致异常：
AttributeError: 'nonetype' object has no attribute 'dtype'
我假设AttributeError是因为pandas不会自动尝试转换/截断浮点值为整数？
我在一个32位的机器上运行32位版本的Python。
>>> !uname -a
Linux ubuntu 3.0.0-13-generic #22-Ubuntu SMP Wed Nov 2 13:25:36 UTC 2011 i686 i686 i386 GNU/Linux
>>> import platform
>>> platform.architecture()
('32bit','ELF')
>>> pandas.__version__
'0.10.1'
解决方法
0.10.1并不真正支持float32
见http://pandas.pydata.org/pandas-docs/dev/whatsnew.html#dtype-specification
你可以在0.11这样做：
# dont' use dtype converters explicity for the columns you care about
# they will be converted to float64 if possible,or object if they cannot
df = pd.read_csv('test.csv'.....)
#### this is optional and related to the issue you posted ####
# force anything that is not a numeric to nan
# columns are the list of columns that you are interesetd in
df[columns] = df[columns].convert_objects(convert_numeric=True)
# astype
df[columns] = df[columns].astype('float32')
see http://pandas.pydata.org/pandas-docs/dev/basics.html#object-conversion
Its not as efficient as doing it directly in read_csv (but that requires
我已经确认用0.11-dev，这个DOES工作(对32位和64位，结果是一样的)
In [5]: x = pd.read_csv(StringIO.StringIO(data),dtype={'a': np.float32},delim_whitespace=True)
In [6]: x
Out[6]:
a b
0 0.76398 0.81394
1 0.32136 0.91063
In [7]: x.dtypes
Out[7]:
a float32
b float64
dtype: object
In [8]: pd.__version__
Out[8]: '0.11.0.dev-385ff82'
In [9]: quit()
vagrant@precise32:~/pandas$ uname -a
Linux precise32 3.2.0-23-generic-pae #36-Ubuntu SMP Tue Apr 10 22:19:09 UTC 2012 i686 i686 i386 GNU/Linux
some low-level changes)
我们今天的关于类型错误：'numpy.float32' 对象不可调用和python中对象不可调用的分享就到这里，谢谢您的阅读，如果想了解更多关于'AttributeError：'numpy.float32'对象没有属性'ctypes'、DJANGO：类型错误“需要一个整数”并且类型错误“bool”对象不可调用、Julia Flux 错误：MethodError：没有方法匹配 *(::Chain{Tuple{Conv{2,4,typeof(identity),Array{Float32,4},Array{Float32,1}},var"#13#15" }}, ::Int64)、numpy – 在pandas 0.10.1上使用pandas.read_csv指定dtype float32的相关信息，可以在本站进行搜索。
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