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image-compression
Commit fb71a265 authored by Bryce Hepner's avatar Bryce Hepner
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Testing for camera information

parent e426ec6e
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Showing with 102 additions and 1 deletion
ExtractPatentTitles.ipynb 0 → 100644
View file @ fb71a265
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import requests\n",
"from bs4 import BeautifulSoup\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"patentlist=[\"GB2174291\",\"DE602007050763.4\",\"CN20519047\",\"FR2174291\",\"US10230909\",\"US10677656\",\"US10393575\",\"KR2411479\",\"UCZL201690000486.1\",\"IL253348\",\"UCZL201721259707.X\",\"US10122944\",\"CN201680041040.8\",\"US10706514\",\"USD875153\",\"CNZL201630601367.9\",\"US10161803\",\"UCZL201590000839.3\",\"UC201590000919.9\",\"CN201480075793.1\",\"US9891817\",\"US5556152\",\"US10070074\",\"US10345436\",\"UCZL201490001097.1\",\"US10054718\",\"US7329869\",\"DE112006002383\",\"FR2719167\",\"GB2719167\",\"DE2719167\",\"CN28553107\",\"US10491787\",\"DE602014031816\",\"FR3031033\",\"FR2898670\",\"DE2898670\",\"US10965894\",\"GB3031033\",\"US10962420\",\"US11031432\",\"CN4285029\",\"US9215384\",\"IL203123\",\"CN101802866\",\"DE1478909\",\"GB1478909\",\"US9436367\",\"CN201410721248.7\",\"US9897645\",\"CN201380059705.4\",\"UCZL201390001075.0\",\"US9367219\",\"CN105027557\",\"UCZL201390001120.2\",\"US10182195\",\"UCZL201520743692.9\",\"UCZL201520744056.8\",\"US10153204\",\"UCZL201390000878.4\",\"CNZL201380059706.9\",\"US9945729\",\"UCZL201520382161.1\",\"US9961277\",\"US9900526\",\"FR1478909\",\"CNZL201080018803.X\",\"CN201180045548.2\",\"US9207662\",\"KR101808375\",\"CN201280038760.0\",\"US9235876\",\"US9208542\",\"US9716844\",\"US9706139\",\"US8378290\",\"US9491376\",\"US8373757\",\"US8552375\",\"US8208026\",\"US9237284\",\"US8780208\",\"US9513172\",\"US7884485\",\"US7679048\",\"US6812465\",\"JP3961486\",\"US7034301\",\"US8049163\",\"US8729474\",\"DE602018026049\",\"GB3574641\",\"EM015607311\",\"GB015607311\",\"GB2939413\",\"UCZL201890000657.X\",\"US10996542\",\"FR2939413\",\"CN5050652\",\"US11012647\",\"US11100618\",\"US11032507\",\"CN201880062374.2\",\"US10986288\",\"FR3152537\",\"GB3152537\",\"DE3152537\",\"US11212466\"]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"newlist = []\n",
"for i, item in enumerate(patentlist):\n",
" if \"US\" in item:\n",
" newlist.append(item)\n",
"titles = []\n",
"for j, i in enumerate(newlist):\n",
" # print(i)\n",
" # print(\"https://patents.google.com/patent/\" + i + \"/\")\n",
" page = requests.get(\"https://patents.google.com/patent/\" + i + \"/\")\n",
" # print(page.text)\n",
" soup = BeautifulSoup(page.content, 'html.parser')\n",
" titles.append(soup.find(\"title\").string)\n",
" time.sleep(2)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['US10230909B2 - Modular split-processing infrared imaging system \\n - Google Patents', 'US10677656B2 - Devices and methods for infrared reference pixels \\n - Google Patents', 'US10393575B2 - Liquid shutter for infrared imaging devices \\n - Google Patents', 'US10122944B2 - Low power and small form factor infrared imaging \\n - Google Patents', 'US10706514B2 - Systems and methods for enhanced dynamic range infrared imaging \\n - Google Patents', 'USD875153S1 - Camera core \\n - Google Patents', 'US10161803B2 - Wafer level packaging of infrared camera detectors \\n - Google Patents', 'US9891817B2 - Processing an infrared (IR) image based on swipe gestures \\n - Google Patents', 'US5556152A - Tailgate \\n - Google Patents', 'US10070074B2 - Vector processing architectures for infrared camera electronics \\n - Google Patents', 'US10345436B2 - System and method for detecting an object or recess on a surface \\n - Google Patents', 'US10054718B2 - Systems and methods for machining materials \\n - Google Patents', 'US7329869B2 - Camera system \\n - Google Patents', 'US10491787B2 - Electrostatic discharge mitigation systems and methods for imaging devices \\n - Google Patents', 'US10965894B2 - Short wave infrared image sensor with automatic exposure and dynamic range control \\n - Google Patents', 'US10962420B2 - Pulse detection and imaging systems and methods \\n - Google Patents', 'US11031432B2 - Vertical microbolometer contact systems and methods \\n - Google Patents', 'US9215384B2 - Method of processing an infrared image, infrared image capturing system and computer readable medium \\n - Google Patents', 'US9436367B2 - Processing an infrared (IR) image based on swipe gestures \\n - Google Patents', 'US9897645B2 - Illuminator for wafer prober and related methods \\n - Google Patents', 'US9367219B2 - Processing an infrared (IR) image based on swipe gestures \\n - Google Patents', 'US10182195B2 - Protective window for an infrared sensor array \\n - Google Patents', 'US10153204B2 - Wafer level packaging of reduced-height infrared detectors \\n - Google Patents', 'US9945729B2 - Systems and methods for enhanced bolometer response \\n - Google Patents', 'US9961277B2 - Infrared focal plane array heat spreaders \\n - Google Patents', 'US9900526B2 - Techniques to compensate for calibration drifts in infrared imaging devices \\n - Google Patents', 'US9207662B2 - Systems and methods for machining materials \\n - Google Patents', 'US9235876B2 - Row and column noise reduction in thermal images \\n - Google Patents', 'US9208542B2 - Pixel-wise noise reduction in thermal images \\n - Google Patents', 'US9716844B2 - Low power and small form factor infrared imaging \\n - Google Patents', 'US9706139B2 - Low power and small form factor infrared imaging \\n - Google Patents', 'US8378290B1 - Sensor calibration systems and methods for infrared cameras \\n - Google Patents', 'US9491376B2 - Flat field correction for infrared cameras \\n - Google Patents', 'US8373757B1 - Flat field correction for infrared cameras \\n - Google Patents', 'US8552375B1 - Switched capacitor filter systems and methods \\n - Google Patents', 'US8208026B2 - Systems and methods for processing infrared images \\n - Google Patents', 'US9237284B2 - Systems and methods for processing infrared images \\n - Google Patents', 'US8780208B2 - Systems and methods for processing infrared images \\n - Google Patents', 'US9513172B2 - Wafer level packaging of infrared camera detectors \\n - Google Patents', 'US7884485B1 - Semiconductor device interconnect systems and methods \\n - Google Patents', 'US7679048B1 - Systems and methods for selecting microbolometers within microbolometer focal plane arrays \\n - Google Patents', 'US6812465B2 - Microbolometer focal plane array methods and circuitry \\n - Google Patents', 'US7034301B2 - Microbolometer focal plane array systems and methods \\n - Google Patents', 'US8049163B1 - Calibration systems and methods for infrared cameras \\n - Google Patents', 'US8729474B1 - Microbolometer contact systems and methods \\n - Google Patents', 'US10996542B2 - Infrared imaging system shutter assembly with integrated thermister \\n - Google Patents', 'US11012647B2 - Low cost and high performance bolometer circuity and methods \\n - Google Patents', 'US11100618B2 - Systems and methods for reducing low-frequency non-uniformity in images \\n - Google Patents', 'US11032507B2 - Frame rate and associated device manufacturing techniques for imaging systems and methods \\n - Google Patents', 'US10986288B2 - Flat field correction systems and methods for infrared cameras \\n - Google Patents', 'US11212466B2 - Multiple microbolometer selection for simultaneous readout \\n - Google Patents']\n"
]
}
],
"source": [
"print(titles)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.10 64-bit",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
}
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"nbformat": 4,
"nbformat_minor": 2
}
FPNprojstart.py → MetadataAnalyzer.py
View file @ fb71a265
...@@ -5,6 +5,8 @@ import pandas as pd ...@@ -5,6 +5,8 @@ import pandas as pd
import statsmodels.api as sm import statsmodels.api as sm
from matplotlib import pyplot as plt from matplotlib import pyplot as plt
from sklearn.metrics import mean_squared_error from sklearn.metrics import mean_squared_error
'''Not externalably usable code because it was just used for internal testing of a few minor things'''
# scenes = file_extractor("images") # scenes = file_extractor("images")
# images = image_extractor(scenes) # images = image_extractor(scenes)
# print(images) # print(images)
...@@ -62,6 +64,7 @@ for i in range(1,3000): ...@@ -62,6 +64,7 @@ for i in range(1,3000):
information_array[i,0] = current_frame_count - frame_count_at_FFC information_array[i,0] = current_frame_count - frame_count_at_FFC
information_array[i,-1] = 4096/np.std(image_array[1:]) information_array[i,-1] = 4096/np.std(image_array[1:])
information_array[i,-2] = mean_squared_error(gaussian_filter(image_array[1:],sigma=.4),image_array[1:]) information_array[i,-2] = mean_squared_error(gaussian_filter(image_array[1:],sigma=.4),image_array[1:])
print(intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[110:111]))
# print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[76:77]) # print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[76:77])
# print("start") # print("start")
# information_array[i,1] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[94:96]) - \ # information_array[i,1] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[94:96]) - \
...@@ -91,7 +94,7 @@ for i in range(1,3000): ...@@ -91,7 +94,7 @@ for i in range(1,3000):
mask = information_array[:,0] > 0 mask = information_array[:,0] > 0
information_df = pd.DataFrame(information_array[mask],columns=["Frame_Spacing","Last_MSE","ImageName","Signal_to_Noise","MSE"]) information_df = pd.DataFrame(information_array[mask],columns=["Frame_Spacing","Last_MSE","ImageName","Signal_to_Noise","MSE"])
information_df.to_csv("smaller_information_weird_array.csv") # information_df.to_csv("smaller_information_weird_array.csv")
information_df = pd.read_csv("smaller_information_weird_array.csv",index_col=0) information_df = pd.read_csv("smaller_information_weird_array.csv",index_col=0)
information_array = information_df.values information_array = information_df.values
print(information_array[0,2]) print(information_array[0,2])
......
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