I am using py_faster_rcnn to train the system for one class ('person'). Originally, it gave me an assertion error similar to this post
How to train new fast-rcnn imageset
So I made the following changes to my imdb.py file:
for b in range(len(boxes)):
if boxes[b][2] < boxes[b][0]:
boxes[b][0] = 0
assert (boxes[:,2] >= boxes[:,0]).all()
After the above changes, I get this new error. Has anyone come across this error or what may I be doing wrong?
Process Process-1:
Traceback (most recent call last):
File "/usr/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/usr/lib/python2.7/multiprocessing/process.py", line 114, in run
self._target(*self._args, **self._kwargs)
File "./tools/train_faster_rcnn_alt_opt.py", line 130, in train_rpn
max_iters=max_iters)
File "/home/microway/test/pytest/py-faster-rcnn/tools/../lib/fast_rcnn/train.py", line 134, in train_net
pretrained_model=pretrained_model)
File "/home/microway/test/pytest/py-faster-rcnn/tools/../lib/fast_rcnn/train.py", line 53, in __init__
self.solver.net.layers[0].set_roidb(roidb)
File "/home/microway/test/pytest/py-faster-rcnn/tools/../lib/roi_data_layer/layer.py", line 68, in set_roidb
self._shuffle_roidb_inds()
File "/home/microway/test/pytest/py-faster-rcnn/tools/../lib/roi_data_layer/layer.py", line 26, in _shuffle_roidb_inds
widths = np.array([r['width'] for r in self._roidb])
KeyError: 'width'
Related
I am using pandas_dedupe library. I get this error when I try to run on a Windows machine, but this same code runs fine on a Mac.
import pandas as pd
import pandas_dedupe as pdd
df=pd.read_csv('sample.csv')
df=pdd.dedupe_dataframe(df,['firstname','lastname','gender','zipcode','address'])
df.to_csv('sample_deduped.csv')
df=df[df['cluster id'].isnull() | ~df[df['cluster id'].notnull()].duplicated(subset='cluster id',keep='first')]
df.to_csv('sample_deuped_removed.csv')
Here are the logs in case you want to have a look:
Traceback (most recent call last):
File "C:/Users/vikas.mittal/Desktop/python projects/untitled2/deduplication.py", line 10, in <module>
df=pdd.dedupe_dataframe(df,['firstname','lastname','gender','zipcode','address'])
File "C:\Users\vikas.mittal\Desktop\python projects\untitled2\venv\lib\site-packages\pandas_dedupe\dedupe_dataframe.py", line 213, in dedupe_dataframe
sample_size)
File "C:\Users\vikas.mittal\Desktop\python projects\untitled2\venv\lib\site-packages\pandas_dedupe\dedupe_dataframe.py", line 72, in _train
dedupe.consoleLabel(deduper)
File "C:\Users\vikas.mittal\Desktop\python projects\untitled2\venv\lib\site-packages\dedupe\convenience.py", line 36, in consoleLabel
uncertain_pairs = deduper.uncertainPairs()
File "C:\Users\vikas.mittal\Desktop\python projects\untitled2\venv\lib\site-packages\dedupe\api.py", line 714, in uncertainPairs
return self.active_learner.pop()
File "C:\Users\vikas.mittal\Desktop\python projects\untitled2\venv\lib\site-packages\dedupe\labeler.py", line 323, in pop
raise IndexError("No more unlabeled examples to label")
IndexError: No more unlabeled examples to label
Process finished with exit code 1
I'm not so sure about the role of the steps parameter in predict_generator, and what I understand is that steps represents the amount of data generated by the generator, but someone denies my answer, and someone confirms my answer
I through the practice still couldn't find the right answer, my way is this, I use openslide to read a 5000x5000 size image, each produced a small map 100x100 to forecast the normal I can read 2500 100x100 the size of the picture, but when I set the steps=2500 is wrong
this is code:
# coding=utf-8
from __future__ import division
from keras.models import load_model
import openslide
import numpy as np
import Get_file_name
import generator
import matplotlib.pyplot as plt
def predict_model(img):
model = load_model(Get_file_name.model_path[0])
y= model.predict_generator(generator.pre_gen(img),steps=30)
print(y)
predict_model("cats_and_dogs_5")
This is wrong：
Exception in thread Thread-1:
Traceback (most recent call last):
File "/usr/lib/python3.5/threading.py", line 914, in _bootstrap_inner
self.run()
File "/usr/lib/python3.5/threading.py", line 862, in run
self._target(*self._args, **self._kwargs)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/training.py", line 612, in data_generator_task
generator_output = next(self._generator)
StopIteration
Traceback (most recent call last):
File "/home/zh/视频/MitosisDetection/mitosisDetection/predict.py", line 17, in <module>
predict_model("cats_and_dogs_5")
File "/home/zh/视频/MitosisDetection/mitosisDetection/predict.py", line 12, in predict_model
y= model.predict_generator(generator.pre_gen(img),steps=2500)
File "/usr/local/lib/python3.5/dist-packages/keras/legacy/interfaces.py", line 88, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/keras/models.py", line 1183, in predict_generator
verbose=verbose)
File "/usr/local/lib/python3.5/dist-packages/keras/legacy/interfaces.py", line 88, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/training.py", line 2108, in predict_generator
outs = self.predict_on_batch(x)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/training.py", line 1696, in predict_on_batch
outputs = self.predict_function(ins)
File "/usr/local/lib/python3.5/dist-packages/keras/backend/tensorflow_backend.py", line 2229, in __call__
feed_dict=feed_dict)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 778, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 961, in _run
% (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape () for Tensor 'conv2d_1_input:0', which has shape '(?, 64, 64, 3)'
Process finished with exit code 1
If steps represents the amount of data generated by my generator, then why do I set steps=2500 wrong? If steps does not represent the amount of data generated by the generator, then what should I do? What should I do to set the amount of data generated by my generator?
Please God more advice, I'm around today, many people do not understand this thing!
I am trying to setup commonsearch and i am the point where backend imports alexa1m data to rocksdb, but it die with error( error below ).
Traceback (most recent call last):
File "urlserver/import.py", line 21, in <module>
ds.import_dump()
File "./urlserver/datasources/__init__.py", line 62, in import_dump
for i, row in self.iter_dump():
File "./urlserver/datasources/__init__.py", line 102, in iter_dump
f = self.open_dump()
File "./urlserver/datasources/__init__.py", line 144, in open_dump
return GzipStreamFile(f)
File "/cosr/back/venv/src/gzipstream/gzipstream/gzipstreamfile.py", line 62, in __init__
super(GzipStreamFile, self).__init__(self._gzipstream)
File "/usr/lib64/python2.6/io.py", line 921, in __init__
raw._checkReadable()
AttributeError: '_GzipStreamFile' object has no attribute '_checkReadable'
have been fighting with this without progress for 2 days now.. if somebody could givme somekind of insight or advice i would be more than happy!
Found the solution, it was problem in the data parsed to the tool, not the tool itself.
I am unable to run django nose tests, all processes fail with this traceback:
Traceback (most recent call last):
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/multiprocessing/process.py", line 114, in run
self._target(*self._args, **self._kwargs)
File "/Users/jeffquinn/Code/Nuna/data-intrawebVE/lib/python2.7/site-packages/nose/plugins/multiprocess.py", line 652, in runner
keyboardCaught, shouldStop, loaderClass, resultClass, config)
File "/Users/jeffquinn/Code/Nuna/data-intrawebVE/lib/python2.7/site-packages/nose/plugins/multiprocess.py", line 669, in __runner
config.plugins.begin()
File "/Users/jeffquinn/Code/Nuna/data-intrawebVE/lib/python2.7/site-packages/nose/plugins/manager.py", line 99, in __call__
return self.call(*arg, **kw)
File "/Users/jeffquinn/Code/Nuna/data-intrawebVE/lib/python2.7/site-packages/nose/plugins/manager.py", line 167, in simple
result = meth(*arg, **kw)
File "/Users/jeffquinn/Code/Nuna/data-intrawebVE/lib/python2.7/site-packages/nose/plugins/cover.py", line 156, in begin
self.coverInstance.exclude('#pragma[: ]+[nN][oO] [cC][oO][vV][eE][rR]')
AttributeError: 'NoneType' object has no attribute 'exclude'
Here are the relevant bits from pip freeze:
Django==1.5.1
MySQL-python==1.2.5
South==0.7.6
Werkzeug==0.8.3
boto==2.8.0
dj-database-url==0.2.1
django-appconf==0.6
django-compressor==1.2
django-extensions==1.0.3
django-json-field==0.5.5
django-nose==1.1
django-storages==1.1.6
django-waffle==0.9.0
djangorestframework==2.1.17
nose==1.3.1
Anyone else seen this? I've seen it mentioned in this pull request (https://github.com/nose-devs/nose/pull/710) but not clear what the solution was.
I just went into the nose source code and commented out lines 156-158.
#self.coverInstance.exclude('#pragma[: ]+[nN][oO] [cC][oO][vV][eE][rR]')
#self.coverInstance.load()
#self.coverInstance.start()
All my tests run fine now. O_o
I'am playing around with scapy but i cant get it to work. I tried different code's but all gave me the same output:
Traceback (most recent call last):
File "<module1>", line 7, in <module>
File "C:\Python26\lib\site-packages\scapy\sendrecv.py", line 357, in srp
s = conf.L2socket(iface=iface, filter=filter, nofilter=nofilter, type=type)
File "C:\Python26\lib\site-packages\scapy\arch\pcapdnet.py", line 313, in __init__
self.outs = dnet.eth(iface)
File "dnet.pyx", line 112, in dnet.eth.__init__
OSError: Result too large
Iam using python 2.6 with all dependencies installed for scapy.
How to fix this?