Deeplab v3+ Shape mismatch in tuple component - python

I have trained deeplab v3+ on ADE20Kdataset,and got the trained ckptjlogs and eventslogs.But when I run eval.pyand vis.pyon ADE20K,I got the following errors about shape:
Shape mismatch in tuple component 1. Expected [513,513,3], got [513,683,3]
These are my evalscripts and vis scripts:
evalscripts:
#!/bin/bash
cd ../
python deeplab/eval.py \
--logtostderr \
--eval_split="val" \
--model_variant="xception_65" \
--atrous_rates=6 \
--atrous_rates=12 \
--atrous_rates=18 \
--output_stride=16 \
--decoder_output_stride=4 \
--eval_crop_size=513 \
--eval_crop_size=513 \
--checkpoint_dir=deeplab/datasets/ADE20K/exp/train_on_train_set/train/ \
--eval_logdir=deeplab/datasets/ADE20K/exp/train_on_train_set/eval/ \
--dataset_dir=deeplab/datasets/ADE20K/tfrecord/ \
--max_number_of_iterations=1
visscripts:
#!/bin/bash
cd ../
python deeplab/vis.py \
--logtostderr \
--vis_split="val" \
--model_variant="xception_65" \
--atrous_rates=6 \
--atrous_rates=12 \
--atrous_rates=18 \
--output_stride=16 \
--decoder_output_stride=4 \
--vis_crop_size=513 \
--vis_crop_size=513 \
--checkpoint_dir=deeplab/datasets/ADE20K/exp/train_on_train_set/train/ \
--vis_logdir=deeplab/datasets/ADE20K/exp/train_on_train_set/vis/ \
--dataset_dir=deeplab/datasets/ADE20K/tfrecord/ \
--max_number_of_iterations=1
And my trainscripts:
#!/bin/bash
cd ../
python deeplab/train.py \
--logtostderr \
--training_number_of_steps=150000 \
--train_split="train" \
--model_variant="xception_65" \
--atrous_rates=6 \
--atrous_rates=12 \
--atrous_rates=18 \
--output_stride=16 \
--decoder_output_stride=4 \
--train_crop_size=513 \
--train_crop_size=513 \
--train_batch_size=2 \
--min_resize_value=513 \
--max_resize_value=513 \
--resize_factor=16 \
--dataset="ade20k" \
--tf_initial_checkpoint=deeplab/datasets/ADE20K/init_models /deeplabv3_xception_ade20k_train/model.ckpt.index \
--train_logdir=deeplab/datasets/ADE20K/exp/train_on_train_set/train \
--dataset_dir=deeplab/datasets/ADE20K/tfrecord/
Is there any thing I set wrong?
Thanks for any help.


Make sure the arguments used in your sh-script match the arguments required by your current code version.
Not long ago you had to pass two separated values for the crop size buy the current implementation uses
--eval_crop_size="513,513" \
or
--vis_crop_size="513,513" \
(taken from here)
Hope this helps ;). If not try to print the crop values in the vis.py/eval.py script and look if the are passed correctly.

Related

Reading Pointcloud from .pcd to ROS PointCloud2

I want to create a simple python script to read some .pcd files and create a sensor_msgs::PointCloud2 for each in a rosbag.
I tried using the python-pcl library, but I'm probably doing something wrong when adding the points to the data field, because when playing the rosbag and checking with RViz and echoing the topic I get no points.
This is the part where I set the PointCloud2 msg.
pcl_data = pcl.load(metadata_dir + "/" + pcd_path)
# get data
pcl_msg = sensor_msgs.msg.PointCloud2()
pcl_msg.data = np.ndarray.tobytes(pcl_data.to_array())
pcl_msg.header.stamp = rospy.Time(t_us/10000000.0)
pcl_msg.header.frame_id = "robot_1/navcam_sensor"
# Pusblish Pointcloud2 msg
outbag.write("/robot_1/pcl_navcam", pcl_msg, rospy.Time(t_us/10000000.0))
I also tried pypc without any luck as well.
How would you do it? Maybe there is a ToROSMsg method somewhere like in the cpp version of pcl?
Is there a python equivalent for what is very easily available in cpp: pcl::toROSMsg ?
Thank you
Here is the full code of the python script:
#! /usr/bin/env python3
import rospy
import rosbag
import tf2_msgs.msg
import geometry_msgs.msg
import sensor_msgs.msg
import sys
import os
import json
import numpy as np
import tf.transformations as tf_transformations
import pcl
import json
import math
import pypcd
import sensor_msgs.point_cloud2 as pc2
import tf2_msgs.msg._TFMessage
def main():
output_bag_path = dataset_path + "rosbag.bag"
with rosbag.Bag(output_bag_path, 'w') as outbag:
# iterate metadata files with tfs
metadata_dir = dataset_path + "Pointcloud/metadata"
t_first_flag = False
# for filename in os.listdir(metadata_dir):
list_of_files = sorted( filter( lambda x: os.path.isfile(os.path.join(metadata_dir, x)),
os.listdir(metadata_dir) ) )
for filename in list_of_files:
# open json file
json_path = os.path.join(metadata_dir, filename)
json_file = open(json_path)
json_data = json.load(json_file)
# get timestamp
t_us = json_data \
["metadata"] \
["Timestamps"] \
["microsec"]
t_ns, t_s = math.modf(t_us/1000000)
# get camera tf
pos = geometry_msgs.msg.Vector3( \
json_data["metadata"] \
["pose_robotFrame_sensorFrame"] \
["data"] \
["translation"][0], \
json_data["metadata"] \
["pose_robotFrame_sensorFrame"] \
["data"] \
["translation"][1], \
json_data["metadata"] \
["pose_robotFrame_sensorFrame"] \
["data"] \
["translation"][2])
quat = geometry_msgs.msg.Quaternion( \
json_data["metadata"] \
["pose_robotFrame_sensorFrame"] \
["data"] \
["orientation"] \
["x"], \
json_data["metadata"] \
["pose_robotFrame_sensorFrame"] \
["data"] \
["orientation"] \
["y"], \
json_data["metadata"] \
["pose_robotFrame_sensorFrame"] \
["data"] \
["orientation"] \
["z"], \
json_data["metadata"] \
["pose_robotFrame_sensorFrame"] \
["data"] \
["orientation"] \
["w"], )
navcam_sensor_tf = geometry_msgs.msg.TransformStamped()
navcam_sensor_tf.header.frame_id = "reu_1/base_link"
navcam_sensor_tf.child_frame_id = "reu_1/navcam_sensor"
navcam_sensor_tf.header.stamp = rospy.Time(t_us/1000000.0)
navcam_sensor_tf.transform.translation = pos
navcam_sensor_tf.transform.rotation = quat
# get base_link tf
pos = geometry_msgs.msg.Vector3( \
json_data["metadata"] \
["pose_fixedFrame_robotFrame"] \
["data"] \
["translation"][0], \
json_data["metadata"] \
["pose_fixedFrame_robotFrame"] \
["data"] \
["translation"][1], \
json_data["metadata"] \
["pose_fixedFrame_robotFrame"] \
["data"] \
["translation"][2])
quat = geometry_msgs.msg.Quaternion( \
json_data["metadata"] \
["pose_fixedFrame_robotFrame"] \
["data"] \
["orientation"] \
["x"], \
json_data["metadata"] \
["pose_fixedFrame_robotFrame"] \
["data"] \
["orientation"] \
["y"], \
json_data["metadata"] \
["pose_fixedFrame_robotFrame"] \
["data"] \
["orientation"] \
["z"], \
json_data["metadata"] \
["pose_fixedFrame_robotFrame"] \
["data"] \
["orientation"] \
["w"], )
base_link_tf = geometry_msgs.msg.TransformStamped()
base_link_tf.header.frame_id = "map"
base_link_tf.child_frame_id = "reu_1/base_link"
base_link_tf.header.stamp = rospy.Time(t_us/1000000.0)
base_link_tf.transform.translation = pos
base_link_tf.transform.rotation = quat
# publish TFs
tf_msg = tf2_msgs.msg.TFMessage()
tf_msg.transforms = []
tf_msg.transforms.append(base_link_tf)
outbag.write("/tf", tf_msg, rospy.Time(t_us/1000000.0))
tf_msg = tf2_msgs.msg.TFMessage()
tf_msg.transforms = []
tf_msg.transforms.append(navcam_sensor_tf)
outbag.write("/tf", tf_msg, rospy.Time(t_us/1000000.0))
# open corresponding .pcd file
pcd_path = json_data["data"]["path"]
pcl_data = pcl.load(metadata_dir + "/" + pcd_path)
# pcl_data = pypcd.(metadata_dir + "/" + pcd_path)
# get data
pcl_msg = sensor_msgs.msg.PointCloud2()
pcl_msg.data = np.ndarray.tobytes(pcl_data.to_array())
pcl_msg.header.stamp = rospy.Time(t_us/1000000.0)# t_s, t_ns)
pcl_msg.header.frame_id = "reu_1/navcam_sensor"
# Pusblish Pointcloud2 msg
outbag.write("/reu_1/pcl_navcam", pcl_msg, rospy.Time(t_us/1000000.0))
pass
if __name__ == "__main__":
dataset_path = "/home/---/Documents/datasets/---/"
main()
The base_link and camera tfs come from a json file that also stores a string to associate the .pcd file.

One issue with the code you posted is that it only creates one PointCloud2 message per file. That being said, there is already a package to do what you're hoping, check out this pcl_ros module. You can create a PointCloud2 message and publish it with rosrun pcl_ros pcd_to_pointcloud <file.pcd> [ <interval> ].
Also as of note: if you're running a full ROS desktop install you don't actually need to install pcl libraries individually; they're baked into the default ROS install.

After using checkpoint in Pyspark the program run faster, why?

My spark setting is like that :
spark_conf = SparkConf().setAppName('app_name') \
.setMaster("local[4]") \
.set('spark.executor.memory', "8g") \
.set('spark.executor.cores', 4) \
.set('spark.task.cpus', 1)
sc = SparkContext.getOrCreate(conf=spark_conf)
sc.setCheckpointDir(dirName='checkpoint')
When I do not have any checkpoint in the spark chain and my program is like this:
result = sc.parallelize(group, 4) \
.map(func_read, preservesPartitioning=True)\
.map(func2,preservesPartitioning=True) \
.flatMap(df_to_dic, preservesPartitioning=True) \
.reduceByKey(func3) \
.map(func4, preservesPartitioning=True) \
.reduceByKey(func5) \
.map(write_to_db) \
.count()
Running time is about 8 hours.
But when I use checkpoint and cache RDD like this:
result = sc.parallelize(group, 4) \
.map(func_read, preservesPartitioning=True)\
.map(func2,preservesPartitioning=True) \
.flatMap(df_to_dic, preservesPartitioning=True) \
.reduceByKey(func3) \
.map(func4, preservesPartitioning=True) \
.reduceByKey(func5) \
.map(write_to_db)
result.cache()
result.checkpoint()
result.count()
The program run in about 3 hours. Would you please guide how it is possible that after caching RDD and using checkpoint the program run faster?
Any help would be really appreciated.

Sphinx Mysql search and indexing with multiple charsets

I was using 'utf8' charset to index and search MySQL db using sphinx. Now I need to index Chinese text too. I'd added charset_table to sphinx conf like this
charset_table = U+F900->U+8C48, U+F901->U+66F4, U+F902->U+8ECA, U+F903->U+8CC8, \
U+F904->U+6ED1, U+F905->U+4E32, U+F906->U+53E5, U+F907->U+9F9C, \
U+F908->U+9F9C, U+F909->U+5951, U+F90A->U+91D1, U+F90B->U+5587, \
U+F90C->U+5948, U+F90D->U+61F6, U+F90E->U+7669, U+F90F->U+7F85, \
U+F910->U+863F, U+F911->U+87BA, U+F912->U+88F8, U+F913->U+908F, \
U+F914->U+6A02, U+F915->U+6D1B, U+F916->U+70D9, U+F917->U+73DE, \
U+F918->U+843D, U+F919->U+916A, U+F91A->U+99F1, U+F91B->U+4E82, \
U+F91C->U+5375, U+F91D->U+6B04, U+F91E->U+721B, U+F91F->U+862D, \
U+F920->U+9E1E, U+F921->U+5D50, U+F922->U+6FEB, U+F923->U+85CD, \
U+F924->U+8964, U+F925->U+62C9, U+F926->U+81D8, U+F927->U+881F, \
U+F928->U+5ECA, U+F929->U+6717, U+F92A->U+6D6A, U+F92B->U+72FC, \
U+F92C->U+90CE, U+F92D->U+4F86, U+F92E->U+51B7, U+F92F->U+52DE, \
U+F930->U+64C4, U+F931->U+6AD3, U+F932->U+7210, U+F933->U+76E7, \
U+F934->U+8001, U+F935->U+8606, U+F936->U+865C, U+F937->U+8DEF, \
U+F938->U+9732, U+F939->U+9B6F, U+F93A->U+9DFA, U+F93B->U+788C, \
U+F93C->U+797F, U+F93D->U+7DA0, U+F93E->U+83C9, U+F93F->U+9304, \
U+F940->U+9E7F, U+F941->U+8AD6, U+F942->U+58DF, U+F943->U+5F04, \
U+F944->U+7C60, U+F945->U+807E, U+F946->U+7262, U+F947->U+78CA, \
U+F948->U+8CC2, U+F949->U+96F7, U+F94A->U+58D8, U+F94B->U+5C62, \
U+F94C->U+6A13, U+F94D->U+6DDA, U+F94E->U+6F0F, U+F94F->U+7D2F, \
U+F950->U+7E37, U+F951->U+964B, U+F952->U+52D2, U+F953->U+808B, \
U+F954->U+51DC, U+F955->U+51CC, U+F956->U+7A1C, U+F957->U+7DBE, \
U+F958->U+83F1, U+F959->U+9675, U+F95A->U+8B80, U+F95B->U+62CF, \
U+F95C->U+6A02, U+F95D->U+8AFE, U+F95E->U+4E39, U+F95F->U+5BE7, \
U+F960->U+6012, U+F961->U+7387, U+F962->U+7570, U+F963->U+5317, \
U+F964->U+78FB, U+F965->U+4FBF, U+F966->U+5FA9, U+F967->U+4E0D, \
U+F968->U+6CCC, U+F969->U+6578, U+F96A->U+7D22, U+F96B->U+53C3, \
U+F96C->U+585E, U+F96D->U+7701, U+F96E->U+8449, U+F96F->U+8AAA, \
U+F970->U+6BBA, U+F971->U+8FB0, U+F972->U+6C88, U+F973->U+62FE, \
U+F974->U+82E5, U+F975->U+63A0, U+F976->U+7565, U+F977->U+4EAE, \
U+F978->U+5169, U+F979->U+51C9, U+F97A->U+6881, U+F97B->U+7CE7, \
U+F97C->U+826F, U+F97D->U+8AD2, U+F97E->U+91CF, U+F97F->U+52F5, \
U+F980->U+5442, U+F981->U+5973, U+F982->U+5EEC, U+F983->U+65C5, \
U+F984->U+6FFE, U+F985->U+792A, U+F986->U+95AD, U+F987->U+9A6A, \
U+F988->U+9E97, U+F989->U+9ECE, U+F98A->U+529B, U+F98B->U+66C6, \
U+F98C->U+6B77, U+F98D->U+8F62, U+F98E->U+5E74, U+F98F->U+6190, \
U+F990->U+6200, U+F991->U+649A, U+F992->U+6F23, U+F993->U+7149, \
U+F994->U+7489, U+F995->U+79CA, U+F996->U+7DF4, U+F997->U+806F, \
U+F998->U+8F26, U+F999->U+84EE, U+F99A->U+9023, U+F99B->U+934A, \
U+F99C->U+5217, U+F99D->U+52A3, U+F99E->U+54BD, U+F99F->U+70C8, \
U+F9A0->U+88C2, U+F9A1->U+8AAA, U+F9A2->U+5EC9, U+F9A3->U+5FF5, \
U+F9A4->U+637B, U+F9A5->U+6BAE, U+F9A6->U+7C3E, U+F9A7->U+7375, \
U+F9A8->U+4EE4, U+F9A9->U+56F9, U+F9AA->U+5BE7, U+F9AB->U+5DBA, \
U+F9AC->U+601C, U+F9AD->U+73B2, U+F9AE->U+7469, U+F9AF->U+7F9A, \
U+F9B0->U+8046, U+F9B1->U+9234, U+F9B2->U+96F6, U+F9B3->U+9748, \
U+F9B4->U+9818, U+F9B5->U+4F8B, U+F9B6->U+79AE, U+F9B7->U+91B4, \
U+F9B8->U+96B8, U+F9B9->U+60E1, U+F9BA->U+4E86, U+F9BB->U+50DA, \
U+F9BC->U+5BEE, U+F9BD->U+5C3F, U+F9BE->U+6599, U+F9BF->U+6A02, \
U+F9C0->U+71CE, U+F9C1->U+7642, U+F9C2->U+84FC, U+F9C3->U+907C, \
U+F9C4->U+9F8D, U+F9C5->U+6688, U+F9C6->U+962E, U+F9C7->U+5289, \
U+F9C8->U+677B, U+F9C9->U+67F3, U+F9CA->U+6D41, U+F9CB->U+6E9C, \
U+F9CC->U+7409, U+F9CD->U+7559, U+F9CE->U+786B, U+F9CF->U+7D10, \
U+F9D0->U+985E, U+F9D1->U+516D, U+F9D2->U+622E, U+F9D3->U+9678, \
U+F9D4->U+502B, U+F9D5->U+5D19, U+F9D6->U+6DEA, U+F9D7->U+8F2A, \
U+F9D8->U+5F8B, U+F9D9->U+6144, U+F9DA->U+6817, U+F9DB->U+7387, \
U+F9DC->U+9686, U+F9DD->U+5229, U+F9DE->U+540F, U+F9DF->U+5C65, \
U+F9E0->U+6613, U+F9E1->U+674E, U+F9E2->U+68A8, U+F9E3->U+6CE5, \
U+F9E4->U+7406, U+F9E5->U+75E2, U+F9E6->U+7F79, U+F9E7->U+88CF, \
U+F9E8->U+88E1, U+F9E9->U+91CC, U+F9EA->U+96E2, U+F9EB->U+533F, \
U+F9EC->U+6EBA, U+F9ED->U+541D, U+F9EE->U+71D0, U+F9EF->U+7498, \U+F9F0->U+85FA, U+F9F1->U+96A3, \
U+F9F2->U+9C57, U+F9F3->U+9E9F, U+F9F4->U+6797, U+F9F5->U+6DCB, U+F9F6->U+81E8, U+F9F7->U+7ACB, \
U+F9F8->U+7B20, U+F9F9->U+7C92, U+F9FA->U+72C0, U+F9FB->U+7099, U+F9FC->U+8B58, U+F9FD->U+4EC0, \
U+F9FE->U+8336, U+F9FF->U+523A, U+FA00->U+5207, U+FA01->U+5EA6, U+FA02->U+62D3, U+FA03->U+7CD6, \
U+FA04->U+5B85, U+FA05->U+6D1E, U+FA06->U+66B4, U+FA07->U+8F3B, U+FA08->U+884C, U+FA09->U+964D, \
U+FA0A->U+898B, U+FA0B->U+5ED3, U+FA0C->U+5140, U+FA0D->U+55C0, U+FA10->U+585A, U+FA12->U+6674, \
U+FA15->U+51DE, U+FA16->U+732A, U+FA17->U+76CA, U+FA18->U+793C, U+FA19->U+795E, U+FA1A->U+7965, \
U+FA1B->U+798F, U+FA1C->U+9756, U+FA1D->U+7CBE, U+FA1E->U+7FBD, U+FA20->U+8612, U+FA22->U+8AF8, \
U+FA25->U+9038, U+FA26->U+90FD, U+FA2A->U+98EF, U+FA2B->U+98FC, U+FA2C->U+9928, U+FA2D->U+9DB4, \
U+FA30->U+4FAE, U+FA31->U+50E7, U+FA32->U+514D, U+FA33->U+52C9, U+FA34->U+52E4, U+FA35->U+5351, \
U+FA36->U+559D, U+FA37->U+5606, U+FA38->U+5668, U+FA39->U+5840, U+FA3A->U+58A8, U+FA3B->U+5C64, \
U+FA3C->U+5C6E, U+FA3D->U+6094, U+FA3E->U+6168, U+FA3F->U+618E, U+FA40->U+61F2, U+FA41->U+654F, \
U+FA42->U+65E2, U+FA43->U+6691, U+FA44->U+6885, U+FA45->U+6D77, U+FA46->U+6E1A, U+FA47->U+6F22, \
U+FA48->U+716E, U+FA49->U+722B, U+FA4A->U+7422, U+FA4B->U+7891, U+FA4C->U+793E, U+FA4D->U+7949, \
U+FA4E->U+7948, U+FA4F->U+7950, U+FA50->U+7956, U+FA51->U+795D, U+FA52->U+798D, U+FA53->U+798E, \
U+FA54->U+7A40, U+FA55->U+7A81, U+FA56->U+7BC0, U+FA57->U+7DF4, U+FA58->U+7E09, U+FA59->U+7E41, \
U+FA5A->U+7F72, U+FA5B->U+8005, U+FA5C->U+81ED, U+FA5D->U+8279, U+FA5E->U+8279, U+FA5F->U+8457, \
U+FA60->U+8910, U+FA61->U+8996, U+FA62->U+8B01, U+FA63->U+8B39, U+FA64->U+8CD3, U+FA65->U+8D08, \
U+FA66->U+8FB6, U+FA67->U+9038, U+FA68->U+96E3, U+FA69->U+97FF, U+FA6A->U+983B, U+FA70->U+4E26, \
U+FA71->U+51B5, U+FA72->U+5168, U+FA73->U+4F80, U+FA74->U+5145, U+FA75->U+5180, U+FA76->U+52C7, \
U+FA77->U+52FA, U+FA78->U+559D, U+FA79->U+5555, U+FA7A->U+5599, U+FA7B->U+55E2, U+FA7C->U+585A, \
U+FA7D->U+58B3, U+FA7E->U+5944, U+FA7F->U+5954, U+FA80->U+5A62, \
U+FA81->U+5B28, U+FA82->U+5ED2, U+FA83->U+5ED9, U+FA84->U+5F69, U+FA85->U+5FAD, U+FA86->U+60D8, \
U+FA87->U+614E, U+FA88->U+6108, U+FA89->U+618E, U+FA8A->U+6160, U+FA8B->U+61F2, U+FA8C->U+6234, \
U+FA8D->U+63C4, U+FA8E->U+641C, U+FA8F->U+6452, U+FA90->U+6556, \
U+FA91->U+6674, U+FA92->U+6717, U+FA93->U+671B, \
U+FA94->U+6756, U+FA95->U+6B79, U+FA96->U+6BBA, U+FA97->U+6D41, U+FA98->U+6EDB, U+FA99->U+6ECB, \
U+FA9A->U+6F22, U+FA9B->U+701E, U+FA9C->U+716E, U+FA9D->U+77A7, U+FA9E->U+7235, U+FA9F->U+72AF, \
U+FAA0->U+732A, U+FAA1->U+7471, U+FAA2->U+7506, U+FAA3->U+753B, U+FAA4->U+761D, U+FAA5->U+761F, \
U+FAA6->U+76CA, U+FAA7->U+76DB, U+FAA8->U+76F4, U+FAA9->U+774A, U+FAAA->U+7740, U+FAAB->U+78CC, \
U+FAAC->U+7AB1, U+FAAD->U+7BC0, U+FAAE->U+7C7B, U+FAAF->U+7D5B, U+FAB0->U+7DF4, U+FAB1->U+7F3E, \
U+FAB2->U+8005, U+FAB3->U+8352, U+FAB4->U+83EF, U+FAB5->U+8779, U+FAB6->U+8941, U+FAB7->U+8986, \
U+FAB8->U+8996, U+FAB9->U+8ABF, U+FABA->U+8AF8, U+FABB->U+8ACB, U+FABC->U+8B01, U+FABD->U+8AFE, \
U+FABE->U+8AED, U+FABF->U+8B39, U+FAC0->U+8B8A, U+FAC1->U+8D08, U+FAC2->U+8F38, U+FAC3->U+9072, \
U+FAC4->U+9199, U+FAC5->U+9276, U+FAC6->U+967C, U+FAC7->U+96E3, U+FAC8->U+9756, U+FAC9->U+97DB, \
U+FACA->U+97FF, U+FACB->U+980B, \
U+FACC->U+983B, U+FACD->U+9B12, U+FACE->U+9F9C, \
U+FACF->U+2284A, U+FAD0->U+22844, U+FAD1->U+233D5, \
U+FAD2->U+3B9D, U+FAD3->U+4018, U+FAD4->U+4039, \
U+FAD5->U+25249, U+FAD6->U+25CD0, U+FAD7->U+27ED3, \
U+FAD8->U+9F43, U+FAD9->U+9F8E, U+2F800->U+4E3D, \
U+2F801->U+4E38, U+2F802->U+4E41, U+2F803->U+20122, \
U+2F804->U+4F60, U+2F805->U+4FAE, U+2F806->U+4FBB, \
U+2F807->U+5002, U+2F808->U+507A, U+2F809->U+5099, \
U+2F80A->U+50E7, U+2F80B->U+50CF, U+2F80C->U+349E, \
U+2F80D->U+2063A, U+2F80E->U+514D, U+2F80F->U+5154, \
U+2F810->U+5164, U+2F811->U+5177, U+2F812->U+2051C, \
U+2F813->U+34B9, U+2F814->U+5167, U+2F815->U+518D, \
U+2F816->U+2054B, U+2F817->U+5197, U+2F818->U+51A4, \
U+2F819->U+4ECC, U+2F81A->U+51AC, U+2F81B->U+51B5, \
U+2F81C->U+291DF, U+2F81D->U+51F5, U+2F81E->U+5203, \
U+2F81F->U+34DF, U+2F820->U+523B, U+2F821->U+5246, \
U+2F822->U+5272, U+2F823->U+5277, U+2F824->U+3515, \
U+2F825->U+52C7, U+2F826->U+52C9, U+2F827->U+52E4, \
U+2F828->U+52FA, U+2F829->U+5305, U+2F82A->U+5306, \
U+2F82B->U+5317, U+2F82C->U+5349, U+2F82D->U+5351, \
U+2F82E->U+535A, U+2F82F->U+5373, U+2F830->U+537D, \
U+2F831->U+537F, U+2F832->U+537F, U+2F833->U+537F, \
U+2F834->U+20A2C, U+2F835->U+7070, U+2F836->U+53CA, \
U+2F837->U+53DF, U+2F838->U+20B63, U+2F839->U+53EB, \
U+2F83A->U+53F1, U+2F83B->U+5406, U+2F83C->U+549E, \
U+2F83D->U+5438, U+2F83E->U+5448, U+2F83F->U+5468, \
U+2F840->U+54A2, U+2F841->U+54F6, U+2F842->U+5510, \
U+2F843->U+5553, U+2F844->U+5563, U+2F845->U+5584, \
U+2F846->U+5584, U+2F847->U+5599, U+2F848->U+55AB, \
U+2F849->U+55B3, U+2F84A->U+55C2, U+2F84B->U+5716, \
U+2F84C->U+5606, U+2F84D->U+5717, U+2F84E->U+5651, \
U+2F84F->U+5674, U+2F850->U+5207, U+2F851->U+58EE, \
U+2F852->U+57CE, U+2F853->U+57F4, U+2F854->U+580D, \
U+2F855->U+578B, U+2F856->U+5832, U+2F857->U+5831, \
U+2F858->U+58AC, U+2F859->U+214E4, U+2F85A->U+58F2, \
U+2F85B->U+58F7, U+2F85C->U+5906, U+2F85D->U+591A, \
U+2F85E->U+5922, U+2F85F->U+5962, U+2F860->U+216A8, \
U+2F861->U+216EA, U+2F862->U+59EC, U+2F863->U+5A1B, \
U+2F864->U+5A27, U+2F865->U+59D8, U+2F866->U+5A66, \
U+2F867->U+36EE, U+2F868->U+36FC, U+2F869->U+5B08, \
U+2F86A->U+5B3E, U+2F86B->U+5B3E, U+2F86C->U+219C8, \
U+2F86D->U+5BC3, U+2F86E->U+5BD8, U+2F86F->U+5BE7, \
U+2F870->U+5BF3, U+2F871->U+21B18, U+2F872->U+5BFF, \
U+2F873->U+5C06, U+2F874->U+5F53, U+2F875->U+5C22, \
U+2F876->U+3781, U+2F877->U+5C60, U+2F878->U+5C6E, \
U+2F879->U+5CC0, U+2F87A->U+5C8D, U+2F87B->U+21DE4, \
U+2F87C->U+5D43, U+2F87D->U+21DE6, U+2F87E->U+5D6E, \
U+2F87F->U+5D6B, U+2F880->U+5D7C, U+2F881->U+5DE1, \
U+2F882->U+5DE2, U+2F883->U+382F, U+2F884->U+5DFD, \
U+2F885->U+5E28, U+2F886->U+5E3D, U+2F887->U+5E69, \
U+2F888->U+3862, U+2F889->U+22183, U+2F88A->U+387C, \
U+2F88B->U+5EB0, U+2F88C->U+5EB3, U+2F88D->U+5EB6, \
U+2F88E->U+5ECA, U+2F88F->U+2A392, U+2F890->U+5EFE, \
U+2F891->U+22331, U+2F892->U+22331, U+2F893->U+8201, \
U+2F894->U+5F22, U+2F895->U+5F22, U+2F896->U+38C7, \
U+2F897->U+232B8, U+2F898->U+261DA, U+2F899->U+5F62, \
U+2F89A->U+5F6B, U+2F89B->U+38E3, U+2F89C->U+5F9A, \
U+2F89D->U+5FCD, U+2F89E->U+5FD7, U+2F89F->U+5FF9, \
U+2F8A0->U+6081, U+2F8A1->U+393A, U+2F8A2->U+391C, \
U+2F8A3->U+6094, U+2F8A4->U+226D4, U+2F8A5->U+60C7, \
U+2F8A6->U+6148, U+2F8A7->U+614C, U+2F8A8->U+614E, \
U+2F8A9->U+614C, U+2F8AA->U+617A, U+2F8AB->U+618E, \
U+2F8AC->U+61B2, U+2F8AD->U+61A4, U+2F8AE->U+61AF, \
U+2F8AF->U+61DE, U+2F8B0->U+61F2, U+2F8B1->U+61F6, \
U+2F8B2->U+6210, U+2F8B3->U+621B, U+2F8B4->U+625D, \
U+2F8B5->U+62B1, U+2F8B6->U+62D4, U+2F8B7->U+6350, \
U+2F8B8->U+22B0C, U+2F8B9->U+633D, U+2F8BA->U+62FC, \
U+2F8BB->U+6368, U+2F8BC->U+6383, U+2F8BD->U+63E4, \
U+2F8BE->U+22BF1, U+2F8BF->U+6422, U+2F8C0->U+63C5, \
U+2F8C1->U+63A9, U+2F8C2->U+3A2E, U+2F8C3->U+6469, \
U+2F8C4->U+647E, U+2F8C5->U+649D, U+2F8C6->U+6477, \
U+2F8C7->U+3A6C, U+2F8C8->U+654F, U+2F8C9->U+656C, \
U+2F8CA->U+2300A, U+2F8CB->U+65E3, U+2F8CC->U+66F8, \
U+2F8CD->U+6649, U+2F8CE->U+3B19, U+2F8CF->U+6691, \
U+2F8D0->U+3B08, U+2F8D1->U+3AE4, U+2F8D2->U+5192, \
U+2F8D3->U+5195, U+2F8D4->U+6700, U+2F8D5->U+669C, \
U+2F8D6->U+80AD, U+2F8D7->U+43D9, U+2F8D8->U+6717, \
U+2F8D9->U+671B, U+2F8DA->U+6721, U+2F8DB->U+675E, \
U+2F8DC->U+6753, U+2F8DD->U+233C3, U+2F8DE->U+3B49, \
U+2F8DF->U+67FA, U+2F8E0->U+6785, U+2F8E1->U+6852, \
U+2F8E2->U+6885, U+2F8E3->U+2346D, U+2F8E4->U+688E, \
U+2F8E5->U+681F, U+2F8E6->U+6914, U+2F8E7->U+3B9D, \
U+2F8E8->U+6942, U+2F8E9->U+69A3, U+2F8EA->U+69EA, \
U+2F8EB->U+6AA8, U+2F8EC->U+236A3, U+2F8ED->U+6ADB, \
U+2F8EE->U+3C18, U+2F8EF->U+6B21, U+2F8F0->U+238A7, \
U+2F8F1->U+6B54, U+2F8F2->U+3C4E, U+2F8F3->U+6B72, \
U+2F8F4->U+6B9F, U+2F8F5->U+6BBA, U+2F8F6->U+6BBB, \
U+2F8F7->U+23A8D, U+2F8F8->U+21D0B, U+2F8F9->U+23AFA, \
U+2F8FA->U+6C4E, U+2F8FB->U+23CBC, U+2F8FC->U+6CBF, \
U+2F8FD->U+6CCD, U+2F8FE->U+6C67, U+2F8FF->U+6D16, \
U+2F900->U+6D3E, U+2F901->U+6D77, U+2F902->U+6D41, \
U+2F903->U+6D69, U+2F904->U+6D78, U+2F905->U+6D85, \
U+2F906->U+23D1E, U+2F907->U+6D34, U+2F908->U+6E2F, \
U+2F909->U+6E6E, U+2F90A->U+3D33, U+2F90B->U+6ECB, \
U+2F90C->U+6EC7, U+2F90D->U+23ED1, U+2F90E->U+6DF9, \
U+2F90F->U+6F6E, U+2F910->U+23F5E, U+2F911->U+23F8E, \
U+2F912->U+6FC6, U+2F913->U+7039, U+2F914->U+701E, \
U+2F915->U+701B, U+2F916->U+3D96, U+2F917->U+704A, \
U+2F918->U+707D, U+2F919->U+7077, U+2F91A->U+70AD, \
U+2F91B->U+20525, U+2F91C->U+7145, U+2F91D->U+24263, \
U+2F91E->U+719C, U+2F91F->U+243AB, U+2F920->U+7228, \
U+2F921->U+7235, U+2F922->U+7250, U+2F923->U+24608, \
U+2F924->U+7280, U+2F925->U+7295, U+2F926->U+24735, \
U+2F927->U+24814, U+2F928->U+737A, U+2F929->U+738B, \
U+2F92A->U+3EAC, U+2F92B->U+73A5, U+2F92C->U+3EB8, \
U+2F92D->U+3EB8, U+2F92E->U+7447, U+2F92F->U+745C, \
U+2F930->U+7471, U+2F931->U+7485, U+2F932->U+74CA, \
U+2F933->U+3F1B, U+2F934->U+7524, U+2F935->U+24C36, \
U+2F936->U+753E, U+2F937->U+24C92, U+2F938->U+7570, \
U+2F939->U+2219F, U+2F93A->U+7610, U+2F93B->U+24FA1, \
U+2F93C->U+24FB8, U+2F93D->U+25044, U+2F93E->U+3FFC, \
U+2F93F->U+4008, U+2F940->U+76F4, U+2F941->U+250F3, \
U+2F942->U+250F2, U+2F943->U+25119, U+2F944->U+25133, \
U+2F945->U+771E, U+2F946->U+771F, U+2F947->U+771F, \
U+2F948->U+774A, U+2F949->U+4039, U+2F94A->U+778B, \
U+2F94B->U+4046, U+2F94C->U+4096, U+2F94D->U+2541D, \
U+2F94E->U+784E, U+2F94F->U+788C, U+2F950->U+78CC, \
U+2F951->U+40E3, U+2F952->U+25626, U+2F953->U+7956, \
U+2F954->U+2569A, U+2F955->U+256C5, U+2F956->U+798F, \
U+2F957->U+79EB, U+2F958->U+412F, U+2F959->U+7A40, \
U+2F95A->U+7A4A, U+2F95B->U+7A4F, U+2F95C->U+2597C, \
U+2F95D->U+25AA7, U+2F95E->U+25AA7, U+2F95F->U+7AEE, \
U+2F960->U+4202, U+2F961->U+25BAB, U+2F962->U+7BC6, \
U+2F963->U+7BC9, U+2F964->U+4227, U+2F965->U+25C80, \
U+2F966->U+7CD2, U+2F967->U+42A0, U+2F968->U+7CE8, \
U+2F969->U+7CE3, U+2F96A->U+7D00, U+2F96B->U+25F86, \
U+2F96C->U+7D63, U+2F96D->U+4301, U+2F96E->U+7DC7, \
U+2F96F->U+7E02, U+2F970->U+7E45, U+2F971->U+4334, \
U+2F972->U+26228, U+2F973->U+26247, U+2F974->U+4359, \
U+2F975->U+262D9, U+2F976->U+7F7A, U+2F977->U+2633E, \
U+2F978->U+7F95, U+2F979->U+7FFA, U+2F97A->U+8005, \
U+2F97B->U+264DA, U+2F97C->U+26523, U+2F97D->U+8060, \
U+2F97E->U+265A8, U+2F97F->U+8070, U+2F980->U+2335F, \
U+2F981->U+43D5, U+2F982->U+80B2, U+2F983->U+8103, \
U+2F984->U+440B, U+2F985->U+813E, U+2F986->U+5AB5, \
U+2F987->U+267A7, U+2F988->U+267B5, U+2F989->U+23393, \
U+2F98A->U+2339C, U+2F98B->U+8201, U+2F98C->U+8204, \
U+2F98D->U+8F9E, U+2F98E->U+446B, U+2F98F->U+8291, \
U+2F990->U+828B, U+2F991->U+829D, U+2F992->U+52B3, \
U+2F993->U+82B1, U+2F994->U+82B3, U+2F995->U+82BD, \
U+2F996->U+82E6, U+2F997->U+26B3C, U+2F998->U+82E5, \
U+2F999->U+831D, U+2F99A->U+8363, U+2F99B->U+83AD, \
U+2F99C->U+8323, U+2F99D->U+83BD, U+2F99E->U+83E7, \
U+2F99F->U+8457, U+2F9A0->U+8353, U+2F9A1->U+83CA, \
U+2F9A2->U+83CC, U+2F9A3->U+83DC, U+2F9A4->U+26C36, \
U+2F9A5->U+26D6B, U+2F9A6->U+26CD5, U+2F9A7->U+452B, \
U+2F9A8->U+84F1, U+2F9A9->U+84F3, U+2F9AA->U+8516, \
U+2F9AB->U+273CA, U+2F9AC->U+8564, U+2F9AD->U+26F2C, \
U+2F9AE->U+455D, U+2F9AF->U+4561, U+2F9B0->U+26FB1, \
U+2F9B1->U+270D2, U+2F9B2->U+456B, U+2F9B3->U+8650, \
U+2F9B4->U+865C, U+2F9B5->U+8667, U+2F9B6->U+8669, \
U+2F9B7->U+86A9, U+2F9B8->U+8688, U+2F9B9->U+870E, \
U+2F9BA->U+86E2, U+2F9BB->U+8779, U+2F9BC->U+8728, \
U+2F9BD->U+876B, U+2F9BE->U+8786, U+2F9BF->U+45D7, \
U+2F9C0->U+87E1, U+2F9C1->U+8801, U+2F9C2->U+45F9, \
U+2F9C3->U+8860, U+2F9C4->U+8863, U+2F9C5->U+27667, \
U+2F9C6->U+88D7, U+2F9C7->U+88DE, U+2F9C8->U+4635, \
U+2F9C9->U+88FA, U+2F9CA->U+34BB, U+2F9CB->U+278AE, \
U+2F9CC->U+27966, U+2F9CD->U+46BE, U+2F9CE->U+46C7, \
U+2F9CF->U+8AA0, U+2F9D0->U+8AED, U+2F9D1->U+8B8A, \
U+2F9D2->U+8C55, U+2F9D3->U+27CA8, U+2F9D4->U+8CAB, \
U+2F9D5->U+8CC1, U+2F9D6->U+8D1B, U+2F9D7->U+8D77, \
U+2F9D8->U+27F2F, U+2F9D9->U+20804, U+2F9DA->U+8DCB, \
U+2F9DB->U+8DBC, U+2F9DC->U+8DF0, U+2F9DD->U+208DE, \
U+2F9DE->U+8ED4, U+2F9DF->U+8F38, U+2F9E0->U+285D2, \
U+2F9E1->U+285ED, U+2F9E2->U+9094, U+2F9E3->U+90F1, \
U+2F9E4->U+9111, U+2F9E5->U+2872E, U+2F9E6->U+911B, \
U+2F9E7->U+9238, U+2F9E8->U+92D7, U+2F9E9->U+92D8, \
U+2F9EA->U+927C, U+2F9EB->U+93F9, U+2F9EC->U+9415, \
U+2F9ED->U+28BFA, U+2F9EE->U+958B, U+2F9EF->U+4995, \
U+2F9F0->U+95B7, U+2F9F1->U+28D77, U+2F9F2->U+49E6, \
U+2F9F3->U+96C3, U+2F9F4->U+5DB2, U+2F9F5->U+9723, \
U+2F9F6->U+29145, U+2F9F7->U+2921A, U+2F9F8->U+4A6E, \
U+2F9F9->U+4A76, U+2F9FA->U+97E0, U+2F9FB->U+2940A, \
U+2F9FC->U+4AB2, U+2F9FD->U+29496, U+2F9FE->U+980B, \
U+2F9FF->U+980B, U+2FA00->U+9829, U+2FA01->U+295B6, \
U+2FA02->U+98E2, U+2FA03->U+4B33, U+2FA04->U+9929, \
U+2FA05->U+99A7, U+2FA06->U+99C2, U+2FA07->U+99FE, \
U+2FA08->U+4BCE, U+2FA09->U+29B30, U+2FA0A->U+9B12, \
U+2FA0B->U+9C40, U+2FA0C->U+9CFD, U+2FA0D->U+4CCE, \
U+2FA0E->U+4CED, U+2FA0F->U+9D67, U+2FA10->U+2A0CE, \
U+2FA11->U+4CF8, U+2FA12->U+2A105, U+2FA13->U+2A20E, \
U+2FA14->U+2A291, U+2FA15->U+9EBB, U+2FA16->U+4D56, \
U+2FA17->U+9EF9, U+2FA18->U+9EFE, U+2FA19->U+9F05, \
U+2FA1A->U+9F0F, U+2FA1B->U+9F16, U+2FA1C->U+9F3B, \
U+2FA1D->U+2A600, U+2F00->U+4E00, U+2F01->U+4E28, \
U+2F02->U+4E36, U+2F03->U+4E3F, U+2F04->U+4E59, \
U+2F05->U+4E85, U+2F06->U+4E8C, U+2F07->U+4EA0, \
U+2F08->U+4EBA, U+2F09->U+513F, U+2F0A->U+5165, \
U+2F0B->U+516B, U+2F0C->U+5182, U+2F0D->U+5196, \
U+2F0E->U+51AB, U+2F0F->U+51E0, U+2F10->U+51F5, \
U+2F11->U+5200, U+2F12->U+529B, U+2F13->U+52F9, \
U+2F14->U+5315, U+2F15->U+531A, U+2F16->U+5338, \
U+2F17->U+5341, U+2F18->U+535C, U+2F19->U+5369, \
U+2F1A->U+5382, U+2F1B->U+53B6, U+2F1C->U+53C8, \
U+2F1D->U+53E3, U+2F1E->U+56D7, U+2F1F->U+571F, \
U+2F20->U+58EB, U+2F21->U+5902, U+2F22->U+590A, \
U+2F23->U+5915, U+2F24->U+5927, U+2F25->U+5973, \
U+2F26->U+5B50, U+2F27->U+5B80, U+2F28->U+5BF8, \
U+2F29->U+5C0F, U+2F2A->U+5C22, U+2F2B->U+5C38, \
U+2F2C->U+5C6E, U+2F2D->U+5C71, U+2F2E->U+5DDB, \
U+2F2F->U+5DE5, U+2F30->U+5DF1, U+2F31->U+5DFE, \
U+2F32->U+5E72, U+2F33->U+5E7A, U+2F34->U+5E7F, \
U+2F35->U+5EF4, U+2F36->U+5EFE, U+2F37->U+5F0B, \
U+2F38->U+5F13, U+2F39->U+5F50, U+2F3A->U+5F61, \
U+2F3B->U+5F73, U+2F3C->U+5FC3, U+2F3D->U+6208, \
U+2F3E->U+6236, U+2F3F->U+624B, U+2F40->U+652F, \
U+2F41->U+6534, U+2F42->U+6587, U+2F43->U+6597, \
U+2F44->U+65A4, U+2F45->U+65B9, U+2F46->U+65E0, \
U+2F47->U+65E5, U+2F48->U+66F0, U+2F49->U+6708, \
U+2F4A->U+6728, U+2F4B->U+6B20, U+2F4C->U+6B62, \
U+2F4D->U+6B79, U+2F4E->U+6BB3, U+2F4F->U+6BCB, \
U+2F50->U+6BD4, U+2F51->U+6BDB, U+2F52->U+6C0F, \
U+2F53->U+6C14, U+2F54->U+6C34, U+2F55->U+706B, \
U+2F56->U+722A, U+2F57->U+7236, U+2F58->U+723B, \
U+2F59->U+723F, U+2F5A->U+7247, U+2F5B->U+7259, \
U+2F5C->U+725B, U+2F5D->U+72AC, U+2F5E->U+7384, \
U+2F5F->U+7389, U+2F60->U+74DC, U+2F61->U+74E6, \
U+2F62->U+7518, U+2F63->U+751F, U+2F64->U+7528, \
U+2F65->U+7530, U+2F66->U+758B, U+2F67->U+7592, \
U+2F68->U+7676, U+2F69->U+767D, U+2F6A->U+76AE, \
U+2F6B->U+76BF, U+2F6C->U+76EE, U+2F6D->U+77DB, \
U+2F6E->U+77E2, U+2F6F->U+77F3, U+2F70->U+793A, \
U+2F71->U+79B8, U+2F72->U+79BE, U+2F73->U+7A74, \
U+2F74->U+7ACB, U+2F75->U+7AF9, U+2F76->U+7C73, \
U+2F77->U+7CF8, U+2F78->U+7F36, U+2F79->U+7F51, \
U+2F7A->U+7F8A, U+2F7B->U+7FBD, U+2F7C->U+8001, \
U+2F7D->U+800C, U+2F7E->U+8012, U+2F7F->U+8033, \
U+2F80->U+807F, U+2F81->U+8089, U+2F82->U+81E3, \
U+2F83->U+81EA, U+2F84->U+81F3, U+2F85->U+81FC, \
U+2F86->U+820C, U+2F87->U+821B, U+2F88->U+821F, \
U+2F89->U+826E, U+2F8A->U+8272, U+2F8B->U+8278, \
U+2F8C->U+864D, U+2F8D->U+866B, U+2F8E->U+8840, \
U+2F8F->U+884C, U+2F90->U+8863, U+2F91->U+897E, \
U+2F92->U+898B, U+2F93->U+89D2, U+2F94->U+8A00, \
U+2F95->U+8C37, U+2F96->U+8C46, U+2F97->U+8C55, \
U+2F98->U+8C78, U+2F99->U+8C9D, U+2F9A->U+8D64, \
U+2F9B->U+8D70, U+2F9C->U+8DB3, U+2F9D->U+8EAB, \
U+2F9E->U+8ECA, U+2F9F->U+8F9B, U+2FA0->U+8FB0, \
U+2FA1->U+8FB5, U+2FA2->U+9091, U+2FA3->U+9149, \
U+2FA4->U+91C6, U+2FA5->U+91CC, U+2FA6->U+91D1, \
U+2FA7->U+9577, U+2FA8->U+9580, U+2FA9->U+961C, \
U+2FAA->U+96B6, U+2FAB->U+96B9, U+2FAC->U+96E8, \
U+2FAD->U+9751, U+2FAE->U+975E, U+2FAF->U+9762, \
U+2FB0->U+9769, U+2FB1->U+97CB, U+2FB2->U+97ED, \
U+2FB3->U+97F3, U+2FB4->U+9801, U+2FB5->U+98A8, \
U+2FB6->U+98DB, U+2FB7->U+98DF, U+2FB8->U+9996, \
U+2FB9->U+9999, U+2FBA->U+99AC, U+2FBB->U+9AA8, \
U+2FBC->U+9AD8, U+2FBD->U+9ADF, U+2FBE->U+9B25, \
U+2FBF->U+9B2F, U+2FC0->U+9B32, U+2FC1->U+9B3C, \
U+2FC2->U+9B5A, U+2FC3->U+9CE5, U+2FC4->U+9E75, \
U+2FC5->U+9E7F, U+2FC6->U+9EA5, U+2FC7->U+9EBB, \
U+2FC8->U+9EC3, U+2FC9->U+9ECD, U+2FCA->U+9ED1, \
U+2FCB->U+9EF9, U+2FCC->U+9EFD, U+2FCD->U+9F0E, \
U+2FCE->U+9F13, U+2FCF->U+9F20, U+2FD0->U+9F3B, \
U+2FD1->U+9F4A, U+2FD2->U+9F52, U+2FD3->U+9F8D, \
U+2FD4->U+9F9C, U+2FD5->U+9FA0, U+3042->U+3041, \
U+3044->U+3043, U+3046->U+3045, U+3048->U+3047, \
U+304A->U+3049, U+304C->U+304B, U+304E->U+304D, \
U+3050->U+304F, U+3052->U+3051, U+3054->U+3053, \
U+3056->U+3055, U+3058->U+3057, U+305A->U+3059, \
U+305C->U+305B, U+305E->U+305D, U+3060->U+305F, \
U+3062->U+3061, U+3064->U+3063, U+3065->U+3063, \
U+3067->U+3066, U+3069->U+3068, U+3070->U+306F, \
U+3071->U+306F, U+3073->U+3072, U+3074->U+3072, \
U+3076->U+3075, U+3077->U+3075, U+3079->U+3078, \
U+307A->U+3078, U+307C->U+307B, U+307D->U+307B, \
U+3084->U+3083, U+3086->U+3085, U+3088->U+3087, \
U+308F->U+308E, U+3094->U+3046, U+3095->U+304B, \
U+3096->U+3051, U+30A2->U+30A1, U+30A4->U+30A3, \
U+30A6->U+30A5, U+30A8->U+30A7, U+30AA->U+30A9, \
U+30AC->U+30AB, U+30AE->U+30AD, U+30B0->U+30AF, \
U+30B2->U+30B1, U+30B4->U+30B3, U+30B6->U+30B5, \
U+30B8->U+30B7, U+30BA->U+30B9, U+30BC->U+30BB, \
U+30BE->U+30BD, U+30C0->U+30BF, U+30C2->U+30C1, \
U+30C5->U+30C4, U+30C7->U+30C6, U+30C9->U+30C8, \
U+30D0->U+30CF, U+30D1->U+30CF, U+30D3->U+30D2, \
U+30D4->U+30D2, U+30D6->U+30D5, U+30D7->U+30D5, \
U+30D9->U+30D8, U+30DA->U+30D8, U+30DC->U+30DB, \
U+30DD->U+30DB, U+30E4->U+30E3, U+30E6->U+30E5, \
U+30E8->U+30E7, U+30EF->U+30EE, U+30F4->U+30A6, \
U+30AB->U+30F5, U+30B1->U+30F6, U+30F7->U+30EF, \
U+30F8->U+30F0, U+30F9->U+30F1, U+30FA->U+30F2, \
U+30AF->U+31F0, U+30B7->U+31F1, U+30B9->U+31F2, \
U+30C8->U+31F3, U+30CC->U+31F4, U+30CF->U+31F5, \
U+30D2->U+31F6, U+30D5->U+31F7, U+30D8->U+31F8, \
U+30DB->U+31F9, U+30E0->U+31FA, U+30E9->U+31FB, \
U+30EA->U+31FC, U+30EB->U+31FD, U+30EC->U+31FE, \
U+30ED->U+31FF, U+FF66->U+30F2, U+FF67->U+30A1, \
U+FF68->U+30A3, U+FF69->U+30A5, U+FF6A->U+30A7, \
U+FF6B->U+30A9, U+FF6C->U+30E3, U+FF6D->U+30E5, \
U+FF6E->U+30E7, U+FF6F->U+30C3, U+FF71->U+30A1, \
U+FF72->U+30A3, U+FF73->U+30A5, U+FF74->U+30A7, \
U+FF75->U+30A9, U+FF76->U+30AB, U+FF77->U+30AD, \
U+FF78->U+30AF, U+FF79->U+30B1, U+FF7A->U+30B3, \
U+FF7B->U+30B5, U+FF7C->U+30B7, U+FF7D->U+30B9, \
U+FF7E->U+30BB, U+FF7F->U+30BD, U+FF80->U+30BF, \
U+FF81->U+30C1, U+FF82->U+30C3, U+FF83->U+30C6, \
U+FF84->U+30C8, U+FF85->U+30CA, U+FF86->U+30CB, \
U+FF87->U+30CC, U+FF88->U+30CD, U+FF89->U+30CE, \
U+FF8A->U+30CF, U+FF8B->U+30D2, U+FF8C->U+30D5, \
U+FF8D->U+30D8, U+FF8E->U+30DB, U+FF8F->U+30DE, \
U+FF90->U+30DF, U+FF91->U+30E0, U+FF92->U+30E1, \
U+FF93->U+30E2, U+FF94->U+30E3, U+FF95->U+30E5, \
U+FF96->U+30E7, U+FF97->U+30E9, U+FF98->U+30EA, \
U+FF99->U+30EB, U+FF9A->U+30EC, U+FF9B->U+30ED, \
U+FF9C->U+30EF, U+FF9D->U+30F3, U+FFA0->U+3164, \
U+FFA1->U+3131, U+FFA2->U+3132, U+FFA3->U+3133, \
U+FFA4->U+3134, U+FFA5->U+3135, U+FFA6->U+3136, \
U+FFA7->U+3137, U+FFA8->U+3138, U+FFA9->U+3139, \
U+FFAA->U+313A, U+FFAB->U+313B, U+FFAC->U+313C, \
U+FFAD->U+313D, U+FFAE->U+313E, U+FFAF->U+313F, \
U+FFB0->U+3140, U+FFB1->U+3141, U+FFB2->U+3142, \
U+FFB3->U+3143, U+FFB4->U+3144, U+FFB5->U+3145, \
U+FFB6->U+3146, U+FFB7->U+3147, U+FFB8->U+3148, \
U+FFB9->U+3149, U+FFBA->U+314A, U+FFBB->U+314B, \
U+FFBC->U+314C, U+FFBD->U+314D, U+FFBE->U+314E, \
U+FFC2->U+314F, U+FFC3->U+3150, U+FFC4->U+3151, \
U+FFC5->U+3152, U+FFC6->U+3153, U+FFC7->U+3154, \
U+FFCA->U+3155, U+FFCB->U+3156, U+FFCC->U+3157, \
U+FFCD->U+3158, U+FFCE->U+3159, U+FFCF->U+315A, \
U+FFD2->U+315B, U+FFD3->U+315C, U+FFD4->U+315D, \
U+FFD5->U+315E, U+FFD6->U+315F, U+FFD7->U+3160, \
U+FFDA->U+3161, U+FFDB->U+3162, U+FFDC->U+3163, \
U+3131->U+1100, U+3132->U+1101, U+3133->U+11AA, \
U+3134->U+1102, U+3135->U+11AC, U+3136->U+11AD, \
U+3137->U+1103, U+3138->U+1104, U+3139->U+1105, \
U+313A->U+11B0, U+313B->U+11B1, U+313C->U+11B2, \
U+313D->U+11B3, U+313E->U+11B4, U+313F->U+11B5, \
U+3140->U+111A, U+3141->U+1106, U+3142->U+1107, \
U+3143->U+1108, U+3144->U+1121, U+3145->U+1109, \
U+3146->U+110A, U+3147->U+110B, U+3148->U+110C, \
U+3149->U+110D, U+314A->U+110E, U+314B->U+110F, \
U+314C->U+1110, U+314D->U+1111, U+314E->U+1112, \
U+314F->U+1161, U+3150->U+1162, U+3151->U+1163, \
U+3152->U+1164, U+3153->U+1165, U+3154->U+1166, \
U+3155->U+1167, U+3156->U+1168, U+3157->U+1169, \
U+3158->U+116A, U+3159->U+116B, U+315A->U+116C, \
U+315B->U+116D, U+315C->U+116E, U+315D->U+116F, \
U+315E->U+1170, U+315F->U+1171, U+3160->U+1172, \
U+3161->U+1173, U+3162->U+1174, U+3163->U+1175, \
U+3165->U+1114, U+3166->U+1115, U+3167->U+11C7, \
U+3168->U+11C8, U+3169->U+11CC, U+316A->U+11CE, \
U+316B->U+11D3, U+316C->U+11D7, U+316D->U+11D9, \
U+316E->U+111C, U+316F->U+11DD, U+3170->U+11DF, \
U+3171->U+111D, U+3172->U+111E, U+3173->U+1120, \
U+3174->U+1122, U+3175->U+1123, U+3176->U+1127, \
U+3177->U+1129, U+3178->U+112B, U+3179->U+112C, \
U+317A->U+112D, U+317B->U+112E, U+317C->U+112F, \
U+317D->U+1132, U+317E->U+1136, U+317F->U+1140, \
U+3180->U+1147, U+3181->U+114C, U+3182->U+11F1, \
U+3183->U+11F2, U+3184->U+1157, U+3185->U+1158, \
U+3186->U+1159, U+3187->U+1184, U+3188->U+1185, \
U+3189->U+1188, U+318A->U+1191, U+318B->U+1192, \
U+318C->U+1194, U+318D->U+119E, U+318E->U+11A1, \
U+A490->U+A408, U+A491->U+A1B9, U+4E00..U+9FBB, \
U+3400..U+4DB5, U+20000..U+2A6D6, U+FA0E, U+FA0F, \
U+FA11, U+FA13, U+FA14, U+FA1F, U+FA21, U+FA23, U+FA24, \
U+FA27, U+FA28, U+FA29, U+3105..U+312C, U+31A0..U+31B7, \
U+3041, U+3043, U+3045, U+3047, U+3049, U+304B, \
U+304D, U+304F, U+3051, U+3053, U+3055, U+3057, U+3059, \
U+305B, U+305D, U+305F, U+3061, U+3063, U+3066, \
U+3068, U+306A..U+306F, U+3072, U+3075, U+3078, U+307B, \
U+307E..U+3083, U+3085, U+3087, U+3089..U+308E, \
U+3090..U+3093, U+30A1, U+30A3, U+30A5, U+30A7, U+30A9, \
U+30AD, U+30AF, U+30B3, U+30B5, U+30BB, U+30BD, \
U+30BF, U+30C1, U+30C3, U+30C4, U+30C6, U+30CA, U+30CB, \
U+30CD, U+30CE, U+30DE, U+30DF, U+30E1, U+30E2, \
U+30E3, U+30E5, U+30E7, U+30EE, U+30F0..U+30F3, U+30F5, \
U+30F6, U+31F0, U+31F1, U+31F2, U+31F3, U+31F4, \
U+31F5, U+31F6, U+31F7, U+31F8, U+31F9, U+31FA, U+31FB, \
U+31FC, U+31FD, U+31FE, U+31FF, U+AC00..U+D7A3, \
U+1100..U+1159, U+1161..U+11A2, U+11A8..U+11F9, \
U+A000..U+A48C, U+A492..U+A4C6
My MySQL connection is established like
connection = mysql.connect(host=settings.SPHINX_HOST, port=settings.SPHINX_PORT, charset='utf8')
MySQL character set is like this
sphinxQL>SHOW CHARACTER SET;
+---------+---------------+-------------------+--------+
| Charset | Description | Default collation | Maxlen |
+---------+---------------+-------------------+--------+
| utf8 | UTF-8 Unicode | utf8_general_ci | 3 |
+---------+---------------+-------------------+--------+
I'm not sure how to add big5 to character set in MySQL, or how to achieve indexing of multiple languages in sphinx and mysql, My code works in python.
Please help.

Some of those codepoints will not fit in CHARACTER SET utf8; you must use utf8mb4.
I suggest moving only to utf8mb4 in the database. It may be reasonable for clients to use BIG5 and let MySQL convert during INSERT and SELECT.

tensorflow deeplabv3+ train from scratch train.sh code to recurring 82.2% in VOC val

DATA: VOC 2012 augmented datasets: I am training train_aug with 10582 annotations.
CODE: I am using official deeplabv3+ code.I didn't change the code except bash code.
Pretrained weight: xception_65_imagenet_coco from official zoo
So, this is my train.sh:
python "${WORK_DIR}"/train.py \
--logtostderr \
--train_split="train_aug" \
--model_variant="xception_65" \
--atrous_rates=6 \
--atrous_rates=12 \
--atrous_rates=18 \
--output_stride=16 \
--decoder_output_stride=4 \
--train_crop_size="513,513" \
--train_batch_size=15 \
--training_number_of_steps=30000 \
--fine_tune_batch_norm=False \
--num_clones=5 \
--base_learning_rate=0.007 \
--tf_initial_checkpoint="${COCO_PRE}/x65-b2u1s2p-d48-2-3x256-sc-cr300k_init.ckpt" \
--train_logdir="${TRAIN_LOGDIR}" \
--dataset_dir="${PASCAL_DATASET}"\
--initialize_last_layer=False
Result: I think it should be 82.2% with my configuration.But I got 80%on eval.OS=16 and 80.15% on eval.OS=8 in 30k steps
So my question is : How can I get 82.2%?
edit:09.02.2019:-----------------
I have notice that the fine_tune_batch_norm=false.
and in train.py:
Set to True if one wants to fine-tune the batch norm parameters in
DeepLabv3
So I decide to try fine_tune_batch_norm=true cause training from scratch need to change the BN parameters.
edit------09/07--------------------
Still not working with:
python "${WORK_DIR}"/train.py \
--logtostderr \
--train_split="train_aug" \
--model_variant="xception_65" \
--atrous_rates=6 \
--atrous_rates=12 \
--atrous_rates=18 \
--output_stride=16 \
--decoder_output_stride=4 \
--train_crop_size="513,513" \
--train_batch_size=15 \
--training_number_of_steps=100000 \
--fine_tune_batch_norm=true \
--num_clones=5 \
--base_learning_rate=0.007 \
--tf_initial_checkpoint="${COCO_PRE}/x65-b2u1s2p-d48-2-3x256-sc-cr300k_init.ckpt" \
--train_logdir="${TRAIN_LOGDIR}" \
--dataset_dir="${PASCAL_DATASET}"\
--initialize_last_layer=False
This time the result is even worse.

I reproduce the result. I got 81.5%. I use 40000 steps for the first round, I think 30000 steps might better.
Bash Code:
python "${WORK_DIR}"/train.py \
--logtostderr \
--train_split="train_aug" \
--model_variant="xception_65" \
--atrous_rates=6 \
--atrous_rates=12 \
--atrous_rates=18 \
--output_stride=16 \
--decoder_output_stride=4 \
--train_crop_size="513,513" \
--train_batch_size=24 \
--base_learning_rate=0.007 \
--training_number_of_steps=30000 \
--fine_tune_batch_norm=true \
--num_clones=8 \
--tf_initial_checkpoint="${COCO_PRE}/x65-b2u1s2p-d48-2-3x256-sc-cr300k_init.ckpt" \
--train_logdir="${TRAIN_LOGDIR}" \
--dataset_dir="${PASCAL_DATASET}"\
--initialize_last_layer=true
python "${WORK_DIR}"/train.py \
--logtostderr \
--train_split="train" \
--model_variant="xception_65" \
--atrous_rates=6 \
--atrous_rates=12 \
--atrous_rates=18 \
--output_stride=16 \
--decoder_output_stride=4 \
--train_crop_size="513,513" \
--train_batch_size=24 \
--training_number_of_steps=60000 \
--fine_tune_batch_norm=false \
--num_clones=8 \
--base_learning_rate=0.01 \
--tf_initial_checkpoint="${COCO_PRE}/x65-b2u1s2p-d48-2-3x256-sc-cr300k_init.ckpt" \
--train_logdir="${TRAIN_LOGDIR}" \
--dataset_dir="${PASCAL_DATASET}"\
--initialize_last_layer=true
reference: github

Fastest method to find all item types with python

I have 5 item types that I have to parse thousands of files (approximately 20kb - 75kb) for:
Item Types
SHA1 hashes
ip addresses
domain names
urls (full thing if possible)
email addresses
I currently use regex to find any items of these nature in thousands of files.
python regex is taking a really long time and I was wondering if there is a better method to identify these item types anywhere in any of my text based flat files?
reSHA1 = r"([A-F]|[0-9]|[a-f]){40}"
reIPv4 = r"\b(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)(\.|\[\.\])){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)"
reURL = r"[A-Z0-9\-\.\[\]]+(\.|\[\.\])(XN--CLCHC0EA0B2G2A9GCD|XN--HGBK6AJ7F53BBA|" \
r"XN--HLCJ6AYA9ESC7A|XN--11B5BS3A9AJ6G|XN--MGBERP4A5D4AR|XN--XKC2DL3A5EE0H|XN--80AKHBYKNJ4F|" \
r"XN--XKC2AL3HYE2A|XN--LGBBAT1AD8J|XN--MGBC0A9AZCG|XN--9T4B11YI5A|XN--MGBAAM7A8H|XN--MGBAYH7GPA|" \
r"XN--MGBBH1A71E|XN--FPCRJ9C3D|XN--FZC2C9E2C|XN--YFRO4I67O|XN--YGBI2AMMX|XN--3E0B707E|XN--JXALPDLP|" \
r"XN--KGBECHTV|XN--OGBPF8FL|XN--0ZWM56D|XN--45BRJ9C|XN--80AO21A|XN--DEBA0AD|XN--G6W251D|XN--GECRJ9C|" \
r"XN--H2BRJ9C|XN--J6W193G|XN--KPRW13D|XN--KPRY57D|XN--PGBS0DH|XN--S9BRJ9C|XN--90A3AC|XN--FIQS8S|" \
r"XN--FIQZ9S|XN--O3CW4H|XN--WGBH1C|XN--WGBL6A|XN--ZCKZAH|XN--P1AI|MUSEUM|TRAVEL|AERO|ARPA|ASIA|COOP|" \
r"INFO|JOBS|MOBI|NAME|BIZ|CAT|COM|EDU|GOV|INT|MIL|NET|ORG|PRO|TEL|XXX|AC|AD|AE|AF|AG|AI|AL|AM|AN|AO|AQ|" \
r"AR|AS|AT|AU|AW|AX|AZ|BA|BB|BD|BE|BF|BG|BH|BI|BJ|BM|BN|BO|BR|BS|BT|BV|BW|BY|BZ|CA|CC|CD|CF|CG|CH|CI|CK|" \
r"CL|CM|CN|CO|CR|CU|CV|CW|CX|CY|CZ|DE|DJ|DK|DM|DO|DZ|EC|EE|EG|ER|ES|ET|EU|FI|FJ|FK|FM|FO|FR|GA|GB|GD|GE|" \
r"GF|GG|GH|GI|GL|GM|GN|GP|GQ|GR|GS|GT|GU|GW|GY|HK|HM|HN|HR|HT|HU|ID|IE|IL|IM|IN|IO|IQ|IR|IS|IT|JE|JM|JO|" \
r"JP|KE|KG|KH|KI|KM|KN|KP|KR|KW|KY|KZ|LA|LB|LC|LI|LK|LR|LS|LT|LU|LV|LY|MA|MC|MD|ME|MG|MH|MK|ML|MM|MN|MO|" \
r"MP|MQ|MR|MS|MT|MU|MV|MW|MX|MY|MZ|NA|NC|NE|NF|NG|NI|NL|NO|NP|NR|NU|NZ|OM|PA|PE|PF|PG|PH|PK|PL|PM|PN|PR|" \
r"PS|PT|PW|PY|QA|RE|RO|RS|RU|RW|SA|SB|SC|SD|SE|SG|SH|SI|SJ|SK|SL|SM|SN|SO|SR|ST|SU|SV|SX|SY|SZ|TC|TD|TF|" \
r"TG|TH|TJ|TK|TL|TM|TN|TO|TP|TR|TT|TV|TW|TZ|UA|UG|UK|US|UY|UZ|VA|VC|VE|VG|VI|VN|VU|WF|WS|YE|YT|ZA|ZM|ZW)" \
r"(/\S+)"
reDomain = r"[A-Z0-9\-\.\[\]]+(\.|\[\.\])(XN--CLCHC0EA0B2G2A9GCD|XN--HGBK6AJ7F53BBA|XN--HLCJ6AYA9ESC7A|" \
r"XN--11B5BS3A9AJ6G|XN--MGBERP4A5D4AR|XN--XKC2DL3A5EE0H|XN--80AKHBYKNJ4F|XN--XKC2AL3HYE2A|" \
r"XN--LGBBAT1AD8J|XN--MGBC0A9AZCG|XN--9T4B11YI5A|XN--MGBAAM7A8H|XN--MGBAYH7GPA|XN--MGBBH1A71E|" \
r"XN--FPCRJ9C3D|XN--FZC2C9E2C|XN--YFRO4I67O|XN--YGBI2AMMX|XN--3E0B707E|XN--JXALPDLP|XN--KGBECHTV|" \
r"XN--OGBPF8FL|XN--0ZWM56D|XN--45BRJ9C|XN--80AO21A|XN--DEBA0AD|XN--G6W251D|XN--GECRJ9C|XN--H2BRJ9C|" \
r"XN--J6W193G|XN--KPRW13D|XN--KPRY57D|XN--PGBS0DH|XN--S9BRJ9C|XN--90A3AC|XN--FIQS8S|XN--FIQZ9S|" \
r"XN--O3CW4H|XN--WGBH1C|XN--WGBL6A|XN--ZCKZAH|XN--P1AI|MUSEUM|TRAVEL|AERO|ARPA|ASIA|COOP|INFO|JOBS|" \
r"MOBI|NAME|BIZ|CAT|COM|EDU|GOV|INT|MIL|NET|ORG|PRO|TEL|XXX|AC|AD|AE|AF|AG|AI|AL|AM|AN|AO|AQ|AR|AS|AT" \
r"|AU|AW|AX|AZ|BA|BB|BD|BE|BF|BG|BH|BI|BJ|BM|BN|BO|BR|BS|BT|BV|BW|BY|BZ|CA|CC|CD|CF|CG|CH|CI|CK|CL|CM|" \
r"CN|CO|CR|CU|CV|CW|CX|CY|CZ|DE|DJ|DK|DM|DO|DZ|EC|EE|EG|ER|ES|ET|EU|FI|FJ|FK|FM|FO|FR|GA|GB|GD|GE|GF|GG|" \
r"GH|GI|GL|GM|GN|GP|GQ|GR|GS|GT|GU|GW|GY|HK|HM|HN|HR|HT|HU|ID|IE|IL|IM|IN|IO|IQ|IR|IS|IT|JE|JM|JO|JP|" \
r"KE|KG|KH|KI|KM|KN|KP|KR|KW|KY|KZ|LA|LB|LC|LI|LK|LR|LS|LT|LU|LV|LY|MA|MC|MD|ME|MG|MH|MK|ML|MM|MN|MO|MP" \
r"|MQ|MR|MS|MT|MU|MV|MW|MX|MY|MZ|NA|NC|NE|NF|NG|NI|NL|NO|NP|NR|NU|NZ|OM|PA|PE|PF|PG|PH|PK|PL|PM|PN|PR|" \
r"PS|PT|PW|PY|QA|RE|RO|RS|RU|RW|SA|SB|SC|SD|SE|SG|SH|SI|SJ|SK|SL|SM|SN|SO|SR|ST|SU|SV|SX|SY|SZ|TC|TD|TF" \
r"|TG|TH|TJ|TK|TL|TM|TN|TO|TP|TR|TT|TV|TW|TZ|UA|UG|UK|US|UY|UZ|VA|VC|VE|VG|VI|VN|VU|WF|WS|YE|YT|ZA|" \
r"ZM|ZW)\b"
reEmail = r"\b[A-Za-z0-9._%+-]+(#|\[#\])[A-Za-z0-9.-]+(\.|\[\.\])(XN--CLCHC0EA0B2G2A9GCD|XN--HGBK6AJ7F53BBA|" \
r"XN--HLCJ6AYA9ESC7A|XN--11B5BS3A9AJ6G|XN--MGBERP4A5D4AR|XN--XKC2DL3A5EE0H|XN--80AKHBYKNJ4F|" \
r"XN--XKC2AL3HYE2A|XN--LGBBAT1AD8J|XN--MGBC0A9AZCG|XN--9T4B11YI5A|XN--MGBAAM7A8H|XN--MGBAYH7GPA|" \
r"XN--MGBBH1A71E|XN--FPCRJ9C3D|XN--FZC2C9E2C|XN--YFRO4I67O|XN--YGBI2AMMX|XN--3E0B707E|XN--JXALPDLP|" \
r"XN--KGBECHTV|XN--OGBPF8FL|XN--0ZWM56D|XN--45BRJ9C|XN--80AO21A|XN--DEBA0AD|XN--G6W251D|XN--GECRJ9C|" \
r"XN--H2BRJ9C|XN--J6W193G|XN--KPRW13D|XN--KPRY57D|XN--PGBS0DH|XN--S9BRJ9C|XN--90A3AC|XN--FIQS8S|" \
r"XN--FIQZ9S|XN--O3CW4H|XN--WGBH1C|XN--WGBL6A|XN--ZCKZAH|XN--P1AI|MUSEUM|TRAVEL|AERO|ARPA|ASIA|COOP|" \
r"INFO|JOBS|MOBI|NAME|BIZ|CAT|COM|EDU|GOV|INT|MIL|NET|ORG|PRO|TEL|XXX|AC|AD|AE|AF|AG|AI|AL|AM|AN|AO|AQ|" \
r"AR|AS|AT|AU|AW|AX|AZ|BA|BB|BD|BE|BF|BG|BH|BI|BJ|BM|BN|BO|BR|BS|BT|BV|BW|BY|BZ|CA|CC|CD|CF|CG|CH|CI|CK" \
r"|CL|CM|CN|CO|CR|CU|CV|CW|CX|CY|CZ|DE|DJ|DK|DM|DO|DZ|EC|EE|EG|ER|ES|ET|EU|FI|FJ|FK|FM|FO|FR|GA|GB|GD|GE" \
r"|GF|GG|GH|GI|GL|GM|GN|GP|GQ|GR|GS|GT|GU|GW|GY|HK|HM|HN|HR|HT|HU|ID|IE|IL|IM|IN|IO|IQ|IR|IS|IT|JE|JM|" \
r"JO|JP|KE|KG|KH|KI|KM|KN|KP|KR|KW|KY|KZ|LA|LB|LC|LI|LK|LR|LS|LT|LU|LV|LY|MA|MC|MD|ME|MG|MH|MK|ML|MM|MN" \
r"|MO|MP|MQ|MR|MS|MT|MU|MV|MW|MX|MY|MZ|NA|NC|NE|NF|NG|NI|NL|NO|NP|NR|NU|NZ|OM|PA|PE|PF|PG|PH|PK|PL|PM|" \
r"PN|PR|PS|PT|PW|PY|QA|RE|RO|RS|RU|RW|SA|SB|SC|SD|SE|SG|SH|SI|SJ|SK|SL|SM|SN|SO|SR|ST|SU|SV|SX|SY|SZ|TC" \
r"|TD|TF|TG|TH|TJ|TK|TL|TM|TN|TO|TP|TR|TT|TV|TW|TZ|UA|UG|UK|US|UY|UZ|VA|VC|VE|VG|VI|VN|VU|WF|WS|YE|YT|" \
r"ZA|ZM|ZW)\b"
I am using a
with open(file, 'r') as f:
for m in re.finditer(key, text, re.IGNORECASE):
try:
m = str(m).split('match=')[-1].split("'")[1]
new_file.write(m + '\n')
except:
pass
method to open, find and output to a new file.
Any assistance with speeding up this item and making it more efficient would be grateful.

You probably want:
text = m.group(0)
print(text, file=new_file)

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