CallBack Error updating graph.figure - DASH - callback

New here and to the world of python.
Generating a histogram plot where it changes color when a postcode is selected.
Now I have the main histogram but when the postcode is selected from the dropdown it gives the error. Unable to figure out how to resolve this. I have provided my full code below.
Let me know if more info is required to figure out the error. Something to do with input
import pandas as pd
import plotly.express as px
from dash import Dash, html, dcc, Input, Output
app = Dash(__name__)
app.title = "EGMs in NSW"
# Load your data : br = .....
datalist=pd.read_excel('premises-list-Aug-2022.xlsx',skiprows=[0,1,2])
datalist['Licence type'] = datalist['Licence type'].str.split(" - ").str.get(1)
datalist['Licence type'] = datalist['Licence type'].str.title()
postcode = datalist['Postcode']
postcode = postcode.sort_values(ascending=True)
postcode=list(dict.fromkeys(postcode))
pd.Series(datalist['Postcode'].unique()).sort_values(ascending=True)
def make_histogram_plot():
# Create scatter plot
fig=px.histogram(
data_frame = datalist,
x='Licence type',y='EGMs',color='Postcode',title='EGMs by Licence Type in NSW',
histfunc='avg'
)
fig.update_traces(marker=dict(color="#002664"))
fig.update_layout(
plot_bgcolor='#EAEDF4',
xaxis_title=None,
yaxis_title='Average EGMs'
)
return fig
app.layout = html.Div(children=[
html.Div([
dcc.Dropdown(postcode,value=[], placeholder="Select postcodes", multi=True, id='postcodes')
]),
dcc.Graph(id = 'graph',figure = make_histogram_plot())
])
#app.callback(
Output('graph','figure'),
Input('postcodes','value')
)
def dropdown_changed(postcodes):
if postcodes==[]:
fig = make_histogram_plot()
else:
datalist2 = datalist[datalist['Postcode'].isin(postcodes)],
# Create scatter plot
fig=px.histogram(
data_frame = datalist2,
x='Licence type',y='EGMs',color='Postcode',title='EGMs by Licence Type in NSW',
histfunc='avg'
)
fig.update_traces(marker=dict(color="#002664"))
fig.update_layout(
plot_bgcolor='#EAEDF4',
xaxis_title=None,
yaxis_title='Average EGMs'
)
return fig
# Start the server
if __name__ == '__main__':
app.run_server(debug=True)

Related

unable to get repr for <class 'albumentations.core.composition.compose'>

I am trying to run a code repository downloaded from GitHub as it is mentioned in the instruction of that but getting following error.
TypeError: init() missing 1 required positional argument: 'image_paths'
I am having this error at the code line 63 (preprocessing = preprocessing).
When I srat the program in debug mode I shows following error
unable to get repr for <class 'albumentations.core.composition.compose'>
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
import torch
from skimage import io
from utils import adjust_sar_contrast, compute_building_score, plot_images
sys.path.append('/home/salman/Downloads/SpaceNet_SAR_Buildings_Solutions-master/4-motokimura/tmp/work')
from spacenet6_model.configs.load_config import get_config_with_previous_experiment
from spacenet6_model.datasets import SpaceNet6TestDataset
from spacenet6_model.models import get_model
from spacenet6_model.transforms import get_augmentation, get_preprocess
# select previous experiment to load
exp_id = 14
exp_log_dir = "/home/salman/Downloads/SpaceNet_SAR_Buildings_Solutions-master/4-motokimura/tmp/logs" # None: use default
# select device to which the model is loaded
cuda = True
if cuda:
device = 'cuda'
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
else:
device = 'cpu'
os.environ['CUDA_VISIBLE_DEVICES'] = ''
# overwrite default config with previous experiment
config = get_config_with_previous_experiment(exp_id=exp_id, exp_log_dir=exp_log_dir)
# overwrite additional hyper parameters
config.MODEL.DEVICE = device
config.WEIGHT_ROOT = "/home/salman/Downloads/SpaceNet_SAR_Buildings_Solutions-master/4-motokimura/tmp/weights/"
config.MODEL.WEIGHT = f"/home/salman/Downloads/SpaceNet_SAR_Buildings_Solutions-master/4-motokimura/tmp/weights/exp_{exp_id:04d}/model_best.pth"
config.INPUT.MEAN_STD_DIR = "/home/salman/Downloads/SpaceNet_SAR_Buildings_Solutions-master/4-motokimura/tmp/work/models/image_mean_std/"
config.INPUT.TEST_IMAGE_DIR = "/home/salman/data/SN6_buildings_AOI_11_Rotterdam_test_public/test_public/AOI_11_Rotterdam/SAR-Intensity"
config.INPUT.SAR_ORIENTATION="/home/salman/Downloads/SpaceNet_SAR_Buildings_Solutions-master/4-motokimura/tmp/work/static/SAR_orientations.txt"
config.TRAIN_VAL_SPLIT_DIR="/home/salman/Downloads/data/spacenet6/split"
config.PREDICTION_ROOT="/home/salman/Downloads/data/spacenet6/predictions"
config.POLY_CSV_ROOT="/home/salman/Downloads/data/spacenet6/polygons"
config.CHECKPOINT_ROOT="/home/salman/Downloads/data/spacenet6/ceckpoints"
config.POLY_OUTPUT_PATH="/home/salman/Downloads/data/spacenet6/val_polygons"
config.freeze()
print(config)
model = get_model(config)
model.eval();
from glob import glob
image_paths = glob(os.path.join(config.INPUT.TEST_IMAGE_DIR, "*.tif"))
#print(image_paths)
preprocessing = get_preprocess(config, is_test=True)
augmentation = get_augmentation(config, is_train=False)
test_dataset = SpaceNet6TestDataset(
config,
augmentation=augmentation,
preprocessing=preprocessing
)
test_dataset_vis = SpaceNet6TestDataset(
config,
augmentation=augmentation,
preprocessing=None
)
channel_footprint = config.INPUT.CLASSES.index('building_footprint')
channel_boundary = config.INPUT.CLASSES.index('building_boundary')
score_thresh = 0.5
alpha = 1.0
start_index = 900
N = 20
for i in range(start_index, start_index + N):
image_vis = test_dataset_vis[i]['image']
image = test_dataset[i]['image']
x_tensor = image.unsqueeze(0).to(config.MODEL.DEVICE)
pr_score = model.module.predict(x_tensor)
pr_score = pr_score.squeeze().cpu().numpy()
pr_score_building = compute_building_score(
pr_score[channel_footprint],
pr_score[channel_boundary],
alpha=alpha
)
pr_mask = pr_score_building > score_thresh
rotated = test_dataset[i]['rotated']
if rotated:
image_vis = np.flipud(np.fliplr(image_vis))
pr_mask = np.flipud(np.fliplr(pr_mask))
plot_images(
SAR_intensity_0=(adjust_sar_contrast(image_vis[:, :, 0]), 'gray'),
building_mask_pr=(pr_mask, 'viridis')
)
The function which this code calls is given below:
def get_spacenet6_preprocess(config, is_test):
"""
"""
mean_path = os.path.join(
config.INPUT.MEAN_STD_DIR,
config.INPUT.IMAGE_TYPE,
'mean.npy'
)
mean = np.load(mean_path)
mean = mean[np.newaxis, np.newaxis, :]
std_path = os.path.join(
config.INPUT.MEAN_STD_DIR,
config.INPUT.IMAGE_TYPE,
'std.npy'
)
std = np.load(std_path)
std = std[np.newaxis, np.newaxis, :]
if is_test:
to_tensor = albu.Lambda(
image=functools.partial(_to_tensor)
)
else:
to_tensor = albu.Lambda(
image=functools.partial(_to_tensor),
mask=functools.partial(_to_tensor)
)
preprocess = [
albu.Lambda(
image=functools.partial(
_normalize_image,
mean=mean,
std=std
)
),
to_tensor,
]
return albu.Compose(preprocess)

Download historical prices for multiple stocks

Here's what I tried (from one suggestion in this group):
from pandas_datareader import data as dreader
symbols = ['GOOG', 'AAPL', 'MMM', 'ACN', 'A', 'ADP']
pnls = {i:dreader.DataReader(i,'yahoo','1985-01-01','2016-09-01') for i in symbols}
this is the error
RemoteDataError: Unable to read URL: https://finance.yahoo.com/quote/GOOG/history?period1=473380200&period2=1472768999&interval=1d&frequency=1d&filter=history
Here's another code that does not seem to work:
import time
import datetime
import pandas as pd
tickers = ['TSLA', 'TWTR', 'MSFT', 'GOOG', 'AAPL']
interval = '1d'
period1 = int(time.mktime(datetime.datetime(2021, 1, 1, 23, 59).timetuple()))
period2 = int(time.mktime(datetime.datetime(2022, 5, 31, 23, 59).timetuple()))
xlwriter = pd.ExcelWriter('historicalprices.xlsx', engine='openpyxl')
for ticker in tickers:
query_string = 'https://query1.finance.yahoo.com/v7/finance/download/{ticker}?period1={period1}&period2={period2}&interval={interval}&events=history&includeAdjustedClose=true'
df = pd.read_csv(query_string)
df.to_excel(xlwriter, sheet_name=ticker, index = False)
xlwriter.save()
this is the error:
HTTPError: HTTP Error 500: Internal Server Error
This code works for individual stocks:
yahoo_financials = YahooFinancials('AAPL')
data = yahoo_financials.get_historical_price_data(start_date='2021-12-01', end_date='2022-05-31',
time_interval='daily')
aapl_df = pd.DataFrame(data['AAPL']['prices'])
aapl_df = aapl_df.drop('date', axis=1).set_index('formatted_date')
aapl_df.to_csv('/Users/rangapriyas/Desktop/Prices/AAPL.csv')
I am new to python can anyone help me with a for loop on this above code pls?
Thanks in advance!
This code works for anyone who may benefit:
import yfinance as yf
import pandas as pd
tickers_list = ['AAPL', 'WMT', 'IBM', 'MU', 'BA', 'AXP']
# Fetch the data
import yfinance as yf
data = yf.download(tickers_list,'2015-1-1', '2022-05-31')['Adj Close']
# Print first 5 rows of the data
print(data.head())

object has no attribute 'dlg'

I'm trying to create a plugin for a Uni-subject which will receive a zipcode from a user and return the name of the corresponding location.
I have created the plugin layout, through the Plugin Builder and have designed the graphical interface with QtDesigner https://i.stack.imgur.com/h6k6Q.png . I have also added the .txt file that contains the zipcodes database to the plugin folder.
However, when I reload the plugin it gives me the error "object has no attribute 'dlg'" error message
Could you give me some guidance here and point me to where the problem could be? I am new to plugin development and python. Thanks
The code is this one:
import os
import sys
import qgis.core
from qgis.PyQt import uic
from qgis.PyQt import (
QtCore,
QtWidgets
)
import geocoder
# This loads your .ui file so that PyQt can populate your plugin with the elements from Qt Designer
FORM_CLASS, _ = uic.loadUiType(os.path.join(
os.path.dirname(__file__), 'example_dialog_base.ui'))
class ExampleDialog(QtWidgets.QDialog, FORM_CLASS):
POSTAL_CODES_PATH = ":/plugins/example/todos_cp.txt"
def __init__(self, parent=None):
"""Constructor."""
super(ExampleDialog, self).__init__(parent)
# Set up the user interface from Designer through FORM_CLASS.
# After self.setupUi() you can access any designer object by doing
# self.<objectname>, and you can use autoconnect slots - see
# http://qt-project.org/doc/qt-4.8/designer-using-a-ui-file.html
# #widgets-and-dialogs-with-auto-connect
self.setupUi(self)
#self.QpushButton.clicked.connect(self.print_hello_world)
self.QlineEdit.textChanged.connect(self.toggle_find_button)
self.find_code_btn.clicked.connect(self.execute)
#def print_hello_world(self):
#print('Hello World!')
def toggle_find_button(self):
if self.QlineEdit.text() == "":
self.find_code_btn.setEnabled(False)
else:
self.find_code_btn.setEnabled(True)
def find_record(self, main_code, extension):
file_handler = QtCore.QFile(self.POSTAL_CODES_PATH)
file_handler.open(QtCore.QIODevice.ReadOnly)
stream = QtCore.QTextStream(file_handler)
while not stream.atEnd():
line = stream.readLine()
info = line.split(";")
code1 = info[-3]
code2 = info[-2]
if code1 == main_code and code2 == extension:
result = info
break
else:
raise RuntimeError("Sem resultados")
return result
def handle_layer_creation(self, record):
place_name = record[3]
point = geocode_place_name(place_name)
print("lon: {} - lat: {}".format(point.x(), point.y()))
layer = create_point_layer(
point,
f"found_location_for_{record[-3]}_{record[-2]}",
place_name
)
current_project = qgis.core.QgsProject.instance()
current_project.addMapLayer(layer)
def show_error(self, message):
message_bar = self.iface.messageBar()
message_bar.pushMessage("Error", message, level=message_bar.Critical)
def validate_postal_code(raw_postal_code):
code1, code2 = raw_postal_code.partition("-")[::2]
if code1 == "" or code2 == "":
raise ValueError(
"Incorrect postal code: {!r}".format(raw_postal_code))
return code1, code2
def geocode_place_name(place_name):
geocoder_object = geocoder.osm(place_name)
lon = geocoder_object.json.get("lng")
lat = geocoder_object.json.get("lat")
if lat is None or lon is None:
raise RuntimeError(
"Could not retrieve lon/lat for "
"place: {!r}".format(place_name)
)
point = qgis.core.QgsPointXY(lon, lat)
return point
def create_point_layer(point, layer_name, place_name):
layer = qgis.core.QgsVectorLayer(
"Point?crs=epsg:4326&field=address:string(100)",
layer_name,
"memory"
)
provider = layer.dataProvider()
geometry = qgis.core.QgsGeometry.fromPointXY(point)
feature = qgis.core.QgsFeature()
feature.setGeometry(geometry)
feature.setAttributes([place_name])
provider.addFeatures([feature])
layer.updateExtents()
return layer

Getting Import Error quite randomly when using plotly express and having multiple graphs on one page

Relatively new to Dash, and this is a problem that has been vexing me for months now. I am making a multi-page app that shows some basic data trends using cards, and graphs embedded within cardbody. 30% of the time, the app works well without any errors and the other 70% it throws either one of the following:
ImportError: cannot import name 'ValidatorCache' from partially initialized module 'plotly.validator_cache' (most likely due to a circular import)
OR
ImportError: cannot import name 'Layout' from partially initialized module 'plotly.graph_objects' (most likely due to a circular import)
Both these appear quite randomly and I usually refresh the app to make them go away. But obviously I am doing something wrong. I have a set of dropdowns that trigger callbacks on graphs. I have been wracking my head about this. Any help/leads would be appreciated. The only pattern I see in the errors is they seem to emerge when the plotly express graphs are being called in the callbacks.
What am I doing wrong? I have searched all over online for help but nothing yet.
Sharing with some relevant snippets of code (this may be too long and many parts not important to the question, but to give you a general idea of what I have been working towards)
import dash
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output, State
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
from plotly.subplots import make_subplots
import plotly.express as px
card_content1_1 = [
dbc.CardHeader([dbc.Row([html.H5("SALES VOLUME TREND", className = "font-weight-bold text-success"),
dbc.Button(
html.I(className="fa fa-window-maximize"),
color="success",
id="sales_maximize",
className="ml-auto",
# href="www.cogitaas.com"
)
])]),
dbc.CardBody(
[dcc.Graph(
id='sales_graph',
figure={},
style={'height':'30vh'}
# className="mt-5"
)])]
card_stacked_discount = [
dbc.CardHeader([dbc.Row([html.H5("VOLUMES UNDER DIFFERENT DISCOUNT LEVELS", className="font-weight-bold text-info text-center"),
dbc.Button(
html.I(className="fa fa-window-maximize"),
color="info",
id="discount_maximize",
className="ml-auto",
# href="www.cogitaas.com"
)
])]),
dbc.CardBody(
[dcc.Dropdown(
id = 'stacked_discount_dropdown',
options =stacked_discount_options,
value=stacked_discount_options[0].get('value'),
style={'color':'black'},
# multi=True
),
dcc.Graph(
id='stacked_discount_graph',
figure={},
style={'height':'30vh'}
)])]
cards = html.Div(
[
dbc.Row(
[
dbc.Col(dbc.Card(card_content1_1, color="success", outline=True,
style={'height':'auto'}), width=8),
],
className="mb-4",
),
dbc.Row(
[
dbc.Col(dbc.Card(card_stacked_discount, color="info", outline=True), width=8),
dbc.Col(dbc.Card([
dbc.Row([
dbc.Col(dbc.Card(disc_sub_title, color="info", inverse=True)),
]),
html.Br(),
dbc.Row([
dbc.Col(dbc.Card(disc_sub_card1, color="info", outline=True)),
]),
]), width=4)
],
className="mb-4",
),
]
)
tab1_content = dbc.Card(
dbc.CardBody(
[cards,]
),
className="mt-3",
)
tabs = dbc.Tabs(dbc.Tab(tab1_content, label="Data", label_style={'color':'blue'}, tab_style={"margin-left":"auto"}),])
content = html.Div([
html.Div([tabs]),
],id="page-content")
app.layout = html.Div([dcc.Location(id="url"), content])
#app.callback(
dash.dependencies.Output('sales_graph', 'figure'),
[dash.dependencies.Input('platform-dropdown', 'value'),
dash.dependencies.Input('signature-dropdown', 'value'),
dash.dependencies.Input('franchise-dropdown', 'value'),
dash.dependencies.Input('sales_maximize', 'n_clicks'),
dash.dependencies.Input('time-dropdown', 'value'),
])
def update_sales_graph(plat, sign, fran, maximize, time_per):
print(str(time_per)+"Test")
time_ax=[]
if isinstance(time_per,str):
time_ax.append(time_per)
time_per=time_ax
if (time_per==None) or ('Full Period' in (time_per)):
dff = df[(df.Platform==plat) & (df.Signature==sign) & (df.Franchise==fran)]
elif ('YTD' in time_per):
dff = df[(df.Platform == plat) & (df.Signature == sign) & (df.Franchise == fran) & (df.year==2020)]
else:
dff = df[(df.Platform==plat) & (df.Signature==sign) & (df.Franchise==fran) & (df.Qtr_yr.isin(time_per))]
fig = px.area(dff, x='Date', y='Qty_Orig', color_discrete_sequence=px.colors.qualitative.Dark2)
fig.add_trace(go.Scatter(x=dff['Date'], y=dff['Outliers'], mode = 'markers', name='Outliers',
line=dict(color='darkblue')))
fig.add_trace(go.Scatter(x=dff['Date'], y=dff['bestfit'], name='Long Term Trend',
line=dict(color='darkblue')))
fig.update_layout(font_family="Rockwell",
title={'text': fran + " Volume Trend",
'y': 0.99,
# 'x': 0.15,
# 'xanchor': 'auto',
'yanchor': 'top'
},
legend=dict(
orientation="h",
# y=-.15, yanchor="bottom", x=0.5, xanchor="center"
),
yaxis_visible=False, yaxis_showticklabels=False,
xaxis_title=None,
margin=dict(l=0, r=0, t=0, b=0, pad=0),
plot_bgcolor='White',
paper_bgcolor='White',
)
fig.update_xaxes(showgrid=False, zeroline=True)
fig.update_yaxes(showgrid=False, zeroline=True)
changed_id = [p['prop_id'] for p in dash.callback_context.triggered][0]
if 'maximize' in changed_id:
fig.show()
return fig
#app.callback(
dash.dependencies.Output('stacked_discount_graph', 'figure'),
[dash.dependencies.Input('platform-dropdown', 'value'),
dash.dependencies.Input('signature-dropdown', 'value'),
dash.dependencies.Input('franchise-dropdown', 'value'),
dash.dependencies.Input('discount_maximize', 'n_clicks'),
dash.dependencies.Input('stacked_discount_dropdown', 'value'),
dash.dependencies.Input('time-dropdown', 'value'),
])
def stacked_discount(plat, sign, fran, maximize, sales_days, time_per):
time_ax=[]
if isinstance(time_per,str):
time_ax.append(time_per)
time_per=time_ax
# else:
# time_per=list(time_per)
if (time_per==None) or ('Full Period' in (time_per)):
df_promo = df_promo_vol[(df_promo_vol.Platform==plat) & (df_promo_vol.Signature==sign) & (df_promo_vol.Franchise==fran)]
elif ('YTD' in time_per):
df_promo = df_promo_vol[(df_promo_vol.Platform == plat) & (df_promo_vol.Signature == sign) & (df_promo_vol.Franchise == fran) & (df_promo_vol.Year==2020)]
else:
df_promo = df_promo_vol[(df_promo_vol.Platform==plat) & (df_promo_vol.Signature==sign) & (df_promo_vol.Franchise==fran) & (df_promo_vol.Qtr_yr.isin(time_per))]
color_discrete_map = {
"0 - 10": "orange",
"10 - 15": "green",
"15 - 20": "blue",
"20 - 25": "goldenrod",
"25 - 30": "magenta",
"30 - 35": "red",
"35 - 40": "aqua",
"40 - 45": "violet",
"45 - 50": "brown",
"50 + ": "black"
}
category_orders = {'disc_range': ['0 - 10', '10 - 15', '15 - 20', '20 - 25', '25 - 30', '30 - 35', '35 - 40',
'40 - 45', '45 - 50', '50 + ']}
if (sales_days == None) or (sales_days == 'sales_act'):
fig = px.bar(df_promo, x='start', y='units_shipped', color='disc_range',
color_discrete_map=color_discrete_map,
category_orders=category_orders,
)
else:
fig = px.bar(df_promo, x='start', y='Date', color="disc_range",
color_discrete_map=color_discrete_map,
category_orders=category_orders,
)
fig.update_layout(font_family="Rockwell",
title={'text': fran + " Sales Decomposition",
'y': 0.99,
'x': 0.1,
# 'xanchor': 'auto',
'yanchor': 'top'
},
legend=dict(
orientation="h",
# y=-.15, yanchor="bottom", x=0.5, xanchor="center"
),
# yaxis_visible=False, yaxis_showticklabels=False,
xaxis_title=None,
margin=dict(l=0, r=0, t=30, b=30, pad=0),
plot_bgcolor='White',
paper_bgcolor='White',
)
fig.update_xaxes(showgrid=False, zeroline=True)
fig.update_yaxes(showgrid=False, zeroline=True)
changed_id = [p['prop_id'] for p in dash.callback_context.triggered][0]
if 'maximize' in changed_id:
fig.show()
return fig
Well, it appears I may have stumbled on to an answer. I was using the pretty much the same inputs for multiple callbacks and that could have been causing some interference with the sequencing of inputs. Once I integrated the code into one callback with multiple outputs, the problem seems to have disappeared.
Was dealing with this same issue where everything in my app worked fine, then I made an entirely separate section & callback that started throwing those circular import errors.
Was reluctant to re-arrange my (rightfully) separated callbacks to be just a single one and found you can fix the issue by just simply importing what the script says it's failing to get. In my case, plotly was trying to import the ValidatorCache and Layout so adding these to the top cleared the issue and now my app works as expected. Hope this helps someone experiencing a similar issue.
from plotly.graph_objects import Layout
from plotly.validator_cache import ValidatorCache

how to access variable from another class in python

I would like to access variable lotId & qty_selected in class 'InputDialog' and to be use in class 'Mainwindow'. I did tried to find a solution in net but unable to solve it until now. can anyone show how to make it?
Here is my current code:
from __future__ import division
from skimage.measure import compare_ssim as ssim
import matplotlib.pyplot as plt
import numpy as np
import sys
import os, glob
import cv2
from PyQt4 import QtCore, QtGui, uic
from PyQt4.QtGui import *
from inputdialog import Ui_inputDialog
from mainwindow import Ui_mainWindow
from tkinter import messagebox
class MainWindow(QtGui.QMainWindow, Ui_mainWindow):
def __init__(self, class_input):
QtGui.QMainWindow.__init__(self)
Ui_mainWindow.__init__(self)
Ui_inputDialog.__init__(self)
self.setupUi(self)
self.capture_button.clicked.connect(self.captureImage)
self.display_button.clicked.connect(self.displayImage)
self.deviceBox.activated.connect(self.selectDeviceCombo)
self.startInspectionBtn.clicked.connect(self.enterLotID)
self.display_button.clicked.connect(self.displayResults)
#self.viewResultBtn.clicked.connect(self.viewResults)
self.window2 = None
def enterLotID(self): # Dialog box will ask user to enter lot ID and wafer qty
if self.window2 is None:
self.window2 = InputDialog(self)
self.window2.isModal()
self.window2.show()
# Program need to be loop through a image file in directory
def displayImage(self, ):
os.chdir('c:\\Users\\mohd_faizal4\\Desktop\\Python\\Testing' + '\\' + lotId )
for lotId in glob.glob('*.jpeg'):
print(lotId)
sample_label = 'c:/Users/mohd_faizal4/Desktop/Python/Image/Picture 6.jpg' # Sample image must read from current folder lot ID running the inspection
self.sample_label.setScaledContents(True)
self.sample_label.setPixmap(QtGui.QPixmap(sample_label))
def selectDeviceCombo(self):
self.var_Selected = self.deviceBox.currentText()
#print('The user selected value now is:')
print('Device = ' + self.var_Selected)
if self.var_Selected.lower() == 'xf35':
print("Great! Device Id is - " + self.var_Selected + '!')
source_label ='c:/Users/mohd_faizal4/Desktop/Python/Image/Picture 4.jpg'
self.source_label.setScaledContents(True)
self.source_label.setPixmap(QtGui.QPixmap(source_label))
elif self.var_Selected.lower() == 'xf38':
print("Great! Device Id is - " + self.var_Selected + '!')
source_label ='c:/Users/mohd_faizal4/Desktop/Python/Image/Picture 5.jpg'
self.source_label.setScaledContents(True)
self.source_label.setPixmap(QtGui.QPixmap(source_label))
elif self.var_Selected.lower() == 'x38c':
print("Great! Device Id is - " + self.var_Selected + '!')
source_label ='c:/Users/mohd_faizal4/Desktop/Python/Image/Picture 7.jpg'
self.source_label.setScaledContents(True)
self.source_label.setPixmap(QtGui.QPixmap(source_label))
else:
print("Pls select device id. It's compulsory field!")
def captureImage(self): # Capture image and display on 'Sample' column under Inspection
cam = cv2.VideoCapture(0)
i = 1
while i < int(input(qty_selected)):
ret, frame = cam.read()
cv2.imshow('Please review an image', frame)
if not ret:
break
k = cv2.waitKey(0)
if k%256 == 27:
# ESC pressed
print("Escape hit, closing...")
break
if k % 256 == 32:
# SPACE pressed
img_name = "_{}.jpeg".format(i)
#print (img_name)
cv2.imwrite(img_name, frame)
#cv2.imwrite(os.path.join(dirname, img_name), frame)
print("{}".format(img_name))
i += 1
cam.release()
cv2.destroyAllWindows()
def displayResults(self): #Display image of wafer at 'Result' tab. Simultaneously with 'Inspect'
label_vid01 = 'c:/Users/mohd_faizal4/Desktop/Python/Image/Picture 7.jpg'
self.label_vid01.setScaledContents(True)
self.label_vid01.setPixmap(QtGui.QPixmap(label_vid01))
# A new class for user input dialog to enter lot information
class InputDialog (QtGui.QDialog, Ui_inputDialog):
def __init__(self, parent):
QtGui.QWidget.__init__(self, parent)
self.setupUi(self)
self.okButton.clicked.connect(self.addLotId)
self.okButton.clicked.connect(self.selectWaferQty)
def addLotId(self):
lotId = str(self.strLotId.toPlainText())
self.strLotId.setText(lotId)
print(lotId)
path = 'c:\\Users\\mohd_faizal4\\Desktop\\Python\\Testing' + '\\' + lotId
if not os.path.exists(path):
os.makedirs(path)
else:
messagebox.showwarning('Error','Please enter required information')
QtGui.QMessageBox.show(self)
# User require to select wafer quantity upon enter the lot ID
def selectWaferQty(self):
qty_selected = self.waferQty.currentText()
#print ('The user selected value now is:')
print ('Wafer Qty = ' + qty_selected)
#if self.qty_selected() == '1':
# print('Great! Wafer Qty is - ' + self.qty_selected + '!')
#else:
# print ('Pls select wafer quantity!')
if __name__ == '__main__':
app = QtGui.QApplication(sys.argv)
Window = MainWindow()
Window.show()
sys.exit()
Under the class InputDialog, change lotId and qty_selected to self.lotId and self.qty_selected, respectively. And to access it inside your WindowMain class, try self.window2.lotId and self.window2.qty_selected.