git diff --no-prefix > [path file name]
patch -p0 < [path file name]
function mapValues(obj, fn) { | |
return Object.keys(obj).reduce((result, key) => { | |
result[key] = fn(obj[key], key); | |
return result; | |
}, {}); | |
} | |
function pick(obj, fn) { | |
return Object.keys(obj).reduce((result, key) => { | |
if (fn(obj[key])) { |
Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.
The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.
On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:
####### 1. A low-resolution photo of road signs
I'm going to walk you through the steps for setting up a AWS Lambda to talk to the internet and a VPC. Let's dive in.
So it might be really unintuitive at first but lambda functions have three states.
-- Create a group | |
CREATE ROLE readaccess; | |
-- Grant access to existing tables | |
GRANT USAGE ON SCHEMA public TO readaccess; | |
GRANT SELECT ON ALL TABLES IN SCHEMA public TO readaccess; | |
-- Grant access to future tables | |
ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON TABLES TO readaccess; |
generated at 2020-12-17
📱 Amazon Fire 7 (7", 1024x600, MDPI) AOSP6.0.0 API 23 310.50 MB
📱 Amazon Fire 7 (7", 1024x600, MDPI) AOSP7.1.0 API 25 361.70 MB
📱 Amazon Fire HD 10 (10.1", 1920x1200, HDPI) AOSP9.0 API 28 416.75 MB
If you are getting this in gdb on macOS while trying to run a program:
Unable to find Mach task port for process-id 57573: (os/kern) failure (0x5).
(please check gdb is codesigned - see taskgated(8))
gdbc
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