My code is:
from __future__ import division
from pyomo.environ import *
import openpyxl
import xlrd
import pyutillib
import win32com
model = AbstractModel()
data = DataPortal()
model.A = Set(dimen=2)
model.p = Param(model.A)
data.load(filename='excel.xls', range='PPtable', param=model.p, index=model.A)
instance = model.create_instance(data)
The error I get:
runfile('C:/Users/faube/.spyder-py3/Pyomo Excel test.py', > > >wdir='C:/Users/faube/.spyder-py3')
Traceback (most recent call last):
File ~.spyder-py3\Pyomo Excel test.py:20 in
data.load(filename='excel.xls', range='PPtable',
File ~\Anaconda3\envs\LTSP\lib\site->packages\pyomo\dataportal\DataPortal.py:146 in load
self.connect(**kwds)
File ~\Anaconda3\envs\LTSP\lib\site-> packages\pyomo\dataportal\DataPortal.py:107 in connect
raise IOError("Unknown file format '%s'" % tmp)
OSError: Unknown file format 'xls'
Any idea? Thanks!
Related
I have built a horse human detector using keras CNN on Google colab the model worked and loaded perfectly on colab. Now I am building a flask application while loading he .h5 model file I was getting error
TypeError: __init__() got an unexpected keyword argument 'ragged'
I reinstall keras 2.3.1 using pip and now I am getting a library error
NameError: name 'six' is not defined
my App.py
#Import necessary libraries
from flask import Flask, render_template, request
import numpy as np
import os
from keras.preprocessing.image import load_img
from keras.preprocessing.image import img_to_array
from keras.models import load_model
#load model
model = load_model("predictor.h5" )
print("## model loaded")
def pred_human_horse(model , horse_or_human):
test_image = load_img(horse_or_human , target_size=(150,150)) #resize
print("## Got Image for predicton")
test_image = img_to_array(test_image)/255 #numpy array between 0-1
test_image = np.expand_dims(test_image,axis=0) #4 dimension
result= model.predict(test_image).round(3) #rounding off
pred =np.argmax(result)
print("## Raw results = ",result)
print("## class = ", pred)
if pred==0:
return "Horse"
else:
return "Human"
# Crate flask app
app = Flask(__name__)
#app.route("/",methods=["GET","POST"])
def home():
return render_template("index.html")
#app.route("/predict",methods=["GET","POST"])
def predict():
if request.method=="POST":
#get input image file
file = request.files["image"]
filename= file.filename
print("## File recieved",filename)
#save the file
file_path= os.path.join("static/user_uploaded",filename)
file.save(file_path)
print("## Prediction...")
pred=pred_human_horse(horse_or_human=file_path )
return render_template("predict.html" ,pred_output= pred , user_image=file_path )
if __name__=="__main__":
app.run(threaded=False)
Error I am getting
runfile('F:/INTERNSHIP/Crisp-Metric-MAY21/Human-horse-prediction/app.py', wdir='F:/INTERNSHIP/Crisp-Metric-MAY21/Human-horse-prediction')
Traceback (most recent call last):
File "<ipython-input-26-df590f092cb6>", line 1, in <module>
runfile('F:/INTERNSHIP/Crisp-Metric-MAY21/Human-horse-prediction/app.py', wdir='F:/INTERNSHIP/Crisp-Metric-MAY21/Human-horse-prediction')
File "C:\Users\DANIA NIAZI\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)
File "C:\Users\DANIA NIAZI\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "F:/INTERNSHIP/Crisp-Metric-MAY21/Human-horse-prediction/app.py", line 13, in <module>
model = load_model("predictor.h5" )
File "C:\Users\DANIA NIAZI\Anaconda3\lib\site-packages\keras\engine\saving.py", line 492, in load_wrapper
File "C:\Users\DANIA NIAZI\Anaconda3\lib\site-packages\keras\engine\saving.py", line 582, in load_model
File "C:\Users\DANIA NIAZI\Anaconda3\lib\site-packages\keras\utils\io_utils.py", line 211, in is_supported_type
NameError: name 'six' is not defined
Maybe you should try installing the six package which will be installed when installing Django. Anyway you can install it using:
pip install six
I have submitted a training job to cloud ml. But, it can't find the csv file. it is there in the bucket. this is the code.
# Use scikit-learn to grid search the batch size and epochs
import numpy
from sklearn.model_selection import GridSearchCV
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
def create_model():
model = Sequential()
model.add(Dense(12, input_dim=11, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='nadam', metrics=['accuracy'])
return model
seed = 7
numpy.random.seed(seed)
FIL = "gs://bubbly-hexagon-112008-ml/dataset/mixed.csv"
dataset = numpy.loadtxt(FIL, delimiter=",")
X = dataset[:,0:11]
Y = dataset[:,11]
model = KerasClassifier(build_fn=create_model, verbose=1)
batch_size = [10, 20, 40, 60, 80, 100]
epochs = [10, 50, 100, 500, 1000]
param_grid = dict(batch_size=batch_size, nb_epoch=epochs)
grid = GridSearchCV(estimator=model, param_grid=param_grid, n_jobs=-1)
grid_result = grid.fit(X, Y)
print("Best: %f using %s" % (grid_result.best_score_, grid_result.best_params_))
means = grid_result.cv_results_['mean_test_score']
stds = grid_result.cv_results_['std_test_score']
params = grid_result.cv_results_['params']
for mean, stdev, param in zip(means, stds, params):
print("%f (%f) with: %r" % (mean, stdev, param))
after submitting the job i get this error.
Traceback (most recent call last): File "/usr/lib/python2.7/runpy.py", line 162, in _run_module_as_main "__main__", fname, loader, pkg_name) File "/usr/lib/python2.7/runpy.py", line 72, in _run_code exec code in
run_globals File "/root/.local/lib/python2.7/
site-packages/trainer/task.py", line 18, in <module> dataset = numpy.loadtxt(FIL, delimiter=",") File "/root/.local/lib/python2.7/
site-packages/numpy/lib/npyio.py", line 803, in loadtxt fh = iter(open(fname, 'U')) IOError: [Errno 2] No such file or directory:
'gs://bubbly-hexagon-112008-ml/dataset/mixed.csv'
-The file is in the specified bucket and its permission includes cloud ml as reader.
-I also used gcloud beta ml init-project to initialize the project.
-And i created a new bucket and put the file in there, but got the same error.
-My bucket is in the same region as my submitted job.
Thanks
file_io from tensorflow works great:
from tensorflow.python.lib.io import file_io
import numpy as np
import json
To read a numpy array:
with file_io.FileIO(path_npx, 'rb') as f:
np_arr = np.load( BytesIO(f.read()) )
print(np_arr)
To read a json file:
with file_io.FileIO(path_json, 'r') as f:
print(json.loads(f.read()))
You can't read directly from gfs like that you need to use some sort of io library.
from io import BytesIO
import tensorflow as tf
import numpy as np
from tensorflow.python.lib.io import file_io
FIL = "gs://bubbly-hexagon-112008-ml/dataset/mixed.csv"
f = BytesIO(file_io.read_file_to_string(FIL, binary_mode=True))
data = np.load(f)
I don't think you can read gcs files directly with numpy.
import pandas as pd
import pandas.io.data as web # as we have to use only pandas function
#Second, retrieve the data from, say, Google itself:
stock = web.DataReader('IBM',data_source='yahoo',start='01/01/2011', end='01/01/2013')
# end of question 1
print type(stock) # Class Type is pandas.core.frame.DataFrame
IBM_dataframe = pd.DataFrame(stock)
Traceback (most recent call last):
File "", line 2, in
import pandas.io.data as web # as we have to use only pandas function
File "C:\Anaconda2\lib\site-packages\pandas\io\data.py", line 2, in
"The pandas.io.data module is moved to a separate package "
ImportError: The pandas.io.data module is moved to a separate package (pandas-datareader). After installing the pandas-datareader package (https://github.com/pydata/pandas-datareader), you can change the import from pandas.io import data, wb to from pandas_datareader import data, wb.
import pandas_datareader as web
stock = web.DataReader('IBM',data_source='yahoo',start='01/01/2011', end='01/01/2013')
Traceback (most recent call last):
File "", line 1, in
stock = web.DataReader('IBM',data_source='yahoo',start='01/01/2011', end='01/01/2013')
AttributeError: 'module' object has no attribute 'DataReader'
change the import pandas.io.data as web to import pandas_datareader as web but now not able to get data plz suggest getting error
'module' object has no attribute 'DataReader'
Use the following:
from pandas_datareader import data, wb
DAX = data.DataReader(name='^GDAXI', data_source='yahoo',start='2000-1-1')
Here is my my code
import theano
import numpy
import os
from keras.models import Sequential
model2 = Sequential()
model2.load_weights("/home/console/Desktop/Apu_code/_epoch_0_e199-0.04.hdf5")
'''model = loaded_models('.)'''
print('loaded')
and getting error :
Using Theano backend.
Traceback (most recent call last):
File "try.py", line 7, in <module>
model2.load_weights("/home/console/Desktop/Apu_code/_epoch_0_e199-0.04.hdf5")
File "/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py", line 2369, in load_weights
str(len(flattened_layers)) + ' layers.')
Exception: You are trying to load a weight file containing 12 layers into a model with 0 layers.
I just do
model0 = keras.models.load_model(hdf5Fname)
to load the file into the variable model0 in order to do sth like
prediction0 = model0.predict( image)[0][0]
and so on...
Is there any way to extract text and documentInfo from PDF file uploaded via Google app engine? I want to use PyPDF2, and my code is this:
pdf_file = self.request.POST['file'].file
pdf_reader = pypdf.PdfFileReader(pdf_file)
This gives me error:
Traceback (most recent call last):
....
File "/myrepo/myproj/main.py", line 154, in post
pdf_text = pypdf.PdfFileReader(pdf_file)
File "lib/PyPDF2/pdf.py", line 649, in __init__
self.read(stream)
File "lib/PyPDF2/pdf.py", line 1100, in read
raise utils.PdfReadError, "EOF marker not found"
PdfReadError: EOF marker not found
It gives this error for any file, even for those that can successfully be read from file on the disk via open(filename, 'r')
am i missing something? thanks in advance!
the solution is to use get_uploads from blobstore_handlers.BlobstoreUploadHandler:
from google.appengine.ext.webapp import blobstore_handlers
from cStringIO import StringIO
import PyPDF2
class UploadHandler(blobstore_handlers.BlobstoreUploadHandler):
def post(self):
upload_files = self.get_uploads('file')
blob_info = upload_files[0]
blob_reader = blobstore.BlobReader(blob_info)
blob_content = StringIO(blob_reader.read())
pdf_info = PyPDF2.PdfFileReader(blob_content)