Resume OCR Node.js
The Node.js OCR SDK supports the Resume API.
Using the sample below, we are going to illustrate how to extract the data that we want using the OCR SDK.
Quick-Start
const mindee = require("mindee");
// for TS or modules:
// import * as mindee from "mindee";
// Init a new client
const mindeeClient = new mindee.Client({ apiKey: "my-api-key" });
// Load a file from disk
const inputSource = mindeeClient.docFromPath("/path/to/the/file.ext");
// Parse the file
const apiResponse = mindeeClient.enqueueAndParse(
mindee.product.ResumeV1,
inputSource
);
// Handle the response Promise
apiResponse.then((resp) => {
// print a string summary
console.log(resp.document.toString());
});
Output (RST):
########
Document
########
:Mindee ID: bc80bae0-af75-4464-95a9-2419403c75bf
:Filename: default_sample.jpg
Inference
#########
:Product: mindee/resume v1.0
:Rotation applied: No
Prediction
==========
:Document Language: ENG
:Document Type: RESUME
:Given Names: Christopher
:Surnames: Morgan
:Nationality:
:Email Address: [email protected]
:Phone Number: +44 (0) 20 7666 8555
:Address: 177 Great Portland Street, London W5W 6PQ
:Social Networks:
+----------------------+----------------------------------------------------+
| Name | URL |
+======================+====================================================+
| LinkedIn | linkedin.com/christopher.morgan |
+----------------------+----------------------------------------------------+
:Profession: Senior Web Developer
:Job Applied:
:Languages:
+----------+----------------------+
| Language | Level |
+==========+======================+
| SPA | Fluent |
+----------+----------------------+
| ZHO | Beginner |
+----------+----------------------+
| DEU | Intermediate |
+----------+----------------------+
:Hard Skills: HTML5
PHP OOP
JavaScript
CSS
MySQL
:Soft Skills: Project management
Strong decision maker
Innovative
Complex problem solver
Creative design
Service-focused
:Education:
+-----------------+---------------------------+-----------+----------+---------------------------+-------------+------------+
| Domain | Degree | End Month | End Year | School | Start Month | Start Year |
+=================+===========================+===========+==========+===========================+=============+============+
| Computer Inf... | Bachelor | | | Columbia University, NY | | 2014 |
+-----------------+---------------------------+-----------+----------+---------------------------+-------------+------------+
:Professional Experiences:
+-----------------+------------+---------------------------+-----------+----------+----------------------+-------------+------------+
| Contract Type | Department | Employer | End Month | End Year | Role | Start Month | Start Year |
+=================+============+===========================+===========+==========+======================+=============+============+
| Full-Time | | Luna Web Design, New York | 05 | 2019 | Web Developer | 09 | 2015 |
+-----------------+------------+---------------------------+-----------+----------+----------------------+-------------+------------+
:Certificates:
+------------+--------------------------------+---------------------------+------+
| Grade | Name | Provider | Year |
+============+================================+===========================+======+
| | PHP Framework (certificate)... | | 2014 |
+------------+--------------------------------+---------------------------+------+
| | Programming Languages: Java... | | |
+------------+--------------------------------+---------------------------+------+
Field Types
Standard Fields
These fields are generic and used in several products.
Basic Field
Each prediction object contains a set of fields that inherit from the generic Field
class.
A typical Field
object will have the following attributes:
- value (
number | string
): corresponds to the field value. Can beundefined
if no value was extracted. - confidence (
number
): the confidence score of the field prediction. - boundingBox (
[Point, Point, Point, Point]
): contains exactly 4 relative vertices (points) coordinates of a right rectangle containing the field in the document. - polygon (
Point[]
): contains the relative vertices coordinates (Point
) of a polygon containing the field in the image. - pageId (
number
): the ID of the page, alwaysundefined
when at document-level. - reconstructed (
boolean
): indicates whether an object was reconstructed (not extracted as the API gave it).
Note: A
Point
simply refers to an array of two numbers ([number, number]
).
Aside from the previous attributes, all basic fields have access to a toString()
method that can be used to print their value as a string.
Classification Field
The classification field ClassificationField
does not implement all the basic Field
attributes. It only implements value, confidence and pageId.
Note: a classification field's
value is always a
string`.
String Field
The text field StringField
only has one constraint: its value is a string
(or undefined
).
Specific Fields
Fields which are specific to this product; they are not used in any other product.
Certificates Field
The list of certificates obtained by the candidate.
A ResumeV1Certificate
implements the following attributes:
grade
(string): The grade obtained for the certificate.name
(string): The name of certification.provider
(string): The organization or institution that issued the certificate.year
(string): The year when a certificate was issued or received.
Fields which are specific to this product; they are not used in any other product.
Education Field
The list of the candidate's educational background.
A ResumeV1Education
implements the following attributes:
degreeDomain
(string): The area of study or specialization.degreeType
(string): The type of degree obtained, such as Bachelor's, Master's, or Doctorate.endMonth
(string): The month when the education program or course was completed.endYear
(string): The year when the education program or course was completed.school
(string): The name of the school.startMonth
(string): The month when the education program or course began.startYear
(string): The year when the education program or course began.
Fields which are specific to this product; they are not used in any other product.
Languages Field
The list of languages that the candidate is proficient in.
A ResumeV1Language
implements the following attributes:
language
(string): The language's ISO 639 code.level
(string): The candidate's level for the language.
Possible values include:
- Fluent
- Proficient
- Intermediate
- Beginner
Fields which are specific to this product; they are not used in any other product.
Professional Experiences Field
The list of the candidate's professional experiences.
A ResumeV1ProfessionalExperience
implements the following attributes:
contractType
(string): The type of contract for the professional experience.
Possible values include:
- Full-Time
- Part-Time
- Internship
- Freelance
department
(string): The specific department or division within the company.employer
(string): The name of the company or organization.endMonth
(string): The month when the professional experience ended.endYear
(string): The year when the professional experience ended.role
(string): The position or job title held by the candidate.startMonth
(string): The month when the professional experience began.startYear
(string): The year when the professional experience began.
Fields which are specific to this product; they are not used in any other product.
Social Networks Field
The list of social network profiles of the candidate.
A ResumeV1SocialNetworksUrl
implements the following attributes:
name
(string): The name of the social network.url
(string): The URL of the social network.
Attributes
The following fields are extracted for Resume V1:
Address
address (StringField): The location information of the candidate, including city, state, and country.
console.log(result.document.inference.prediction.address.value);
Certificates
certificates (ResumeV1Certificate[]): The list of certificates obtained by the candidate.
for (const certificatesElem of result.document.inference.prediction.certificates) {
console.log(certificatesElem.value);
}
Document Language
documentLanguage (StringField): The ISO 639 code of the language in which the document is written.
console.log(result.document.inference.prediction.documentLanguage.value);
Document Type
documentType (ClassificationField): The type of the document sent.
Possible values include:
- RESUME
- MOTIVATION_LETTER
- RECOMMENDATION_LETTER
console.log(result.document.inference.prediction.documentType.value);
Education
education (ResumeV1Education[]): The list of the candidate's educational background.
for (const educationElem of result.document.inference.prediction.education) {
console.log(educationElem.value);
}
Email Address
emailAddress (StringField): The email address of the candidate.
console.log(result.document.inference.prediction.emailAddress.value);
Given Names
givenNames (StringField[]): The candidate's first or given names.
for (const givenNamesElem of result.document.inference.prediction.givenNames) {
console.log(givenNamesElem.value);
}
Hard Skills
hardSkills (StringField[]): The list of the candidate's technical abilities and knowledge.
for (const hardSkillsElem of result.document.inference.prediction.hardSkills) {
console.log(hardSkillsElem.value);
}
Job Applied
jobApplied (StringField): The position that the candidate is applying for.
console.log(result.document.inference.prediction.jobApplied.value);
Languages
languages (ResumeV1Language[]): The list of languages that the candidate is proficient in.
for (const languagesElem of result.document.inference.prediction.languages) {
console.log(languagesElem.value);
}
Nationality
nationality (StringField): The ISO 3166 code for the country of citizenship of the candidate.
console.log(result.document.inference.prediction.nationality.value);
Phone Number
phoneNumber (StringField): The phone number of the candidate.
console.log(result.document.inference.prediction.phoneNumber.value);
Profession
profession (StringField): The candidate's current profession.
console.log(result.document.inference.prediction.profession.value);
Professional Experiences
professionalExperiences (ResumeV1ProfessionalExperience[]): The list of the candidate's professional experiences.
for (const professionalExperiencesElem of result.document.inference.prediction.professionalExperiences) {
console.log(professionalExperiencesElem.value);
}
Social Networks
socialNetworksUrls (ResumeV1SocialNetworksUrl[]): The list of social network profiles of the candidate.
for (const socialNetworksUrlsElem of result.document.inference.prediction.socialNetworksUrls) {
console.log(socialNetworksUrlsElem.value);
}
Soft Skills
softSkills (StringField[]): The list of the candidate's interpersonal and communication abilities.
for (const softSkillsElem of result.document.inference.prediction.softSkills) {
console.log(softSkillsElem.value);
}
Surnames
surnames (StringField[]): The candidate's last names.
for (const surnamesElem of result.document.inference.prediction.surnames) {
console.log(surnamesElem.value);
}
Questions?
Updated about 1 month ago