pixelbin 1.0.5

Real-time image transformations with automatic optimization, image URL and storage for efficient image organization

Pixelbin

Pixelbin Dart library helps you integrate Pixelbin with your Dart/Flutter Application.

Usage

Install using Pub Package Manager

Run this command:

• With Dart:

     dart pub add pixelbin

• With Flutter:

     flutter pub add pixelbin

OR

• This will add a line like this to your package's pubspec.yaml (and run an implicit dart pub get):

dependencies:
  pixelbin: ^latest_release_version

Creating Image from URL or Cloud details

import 'package:pixelbin/pixelbin_dart_sdk.dart';
final PixelBinImage? imageFromUrl = PixelBin.shared.imageFromUrl(
        "https://cdn.pixelbin.io/v2/dummy-cloudname/erase.bg(shadow:false,r:true,i:general)~af.remove()~t.blur(s:0.3,dpr:1.0)/__playground/playground-default.jpeg");
debugPrint(imageFromUrl?.encoded);
// Create Image url from cloud, zone and other details
final PixelBinImage imageFromDetails = pixelBin.image(
          imagePath: imageFromUrl.imagePath, cloud: imageFromUrl.cloudName, transformations: imageFromUrl.transformations, version: imageFromUrl.version);
debugPrint(imageFromDetails.encoded);

---

Applying Transformations and Getting Transformations

import 'package:pixelbin/pixelbin_dart_sdk.dart';
// Create Image url from cloud, zone and imagePath on cloud (Not local path)
final image = PixelBin.shared.image(imagePath: "example/logo/apple.jpg", cloud: "apple_cloud", zone: "south_asia");
      debugPrint(imageFromDetails.encoded); // https://cdn.pixelbin.io/v2/apple_cloud/south_asia/original/example/logo/apple.jpg
final resizeTransformation = Transformation.tResize(height: 200, width: 200); // Creating Resize Transformation
image.addTransformations([eraseTransformation, resizeTransformation]); // Applying multiple transformations with list(keep passing all transformations in list)
// OR
image.addTransformation(resizeTransformation); // Applying transformations one by one
final outputUrl = image.encoded; // https://cdn.pixelbin.io/v2/apple_cloud/south_asia/erase.bg()~t.resize(h:100,w:100)/example/logo/apple.jpg
debugPrint(outputUrl);

Uploading Image and getting url object

// Signed Url and Field can be generated via using Backed SDK for pixelbin or API to generate signed url for upload
// Assume imagePath: "example/logo/apple.jpg", cloud: "apple_cloud", zone: "south_asia" & generate details
final signUrl = "SIGNED_URL";
final fields = {// Key: Value}; // META_DATA in value
final signedDetails = SignedDetails(url: signUrl, fields: fields)
// file is local picked file, other fields chunkSize: Int = 1024, concurrency: Int = 1
try {
     final signedDetails = SignedDetails(url: signUrl,fields:fields);
     final PixelBinImage? uploadResponse = await PixelBin.shared
          .upload(file: file, signedDetails: signedDetails);
     debugPrint("Response:=> ${uploadResponse?.encoded}");
    } catch (e) {
     debugPrint("Error:=> ${e.toString()}");
    }

Parameter	Type	Description
file (File)	File	File to upload to Pixelbin
signedDetails (SignedDetails)	Object	Signed details generated with the Pixelbin Backend SDK
chunkSize (Int)	Integer	Size of chunks to be uploaded in KB (default value is 1024)
concurrency (Int)	Integer	Number of chunks to be uploaded in parallel API calls

• Resolves with Image object on success.
• Rejects with error on failure.

List of Supported Transformations

DetectBackgroundType

1. dbtDetect()

Classifies the background of a product as plain, clean or busy

final t = Transformation.dbtDetect(
);

Basic

1. tResize(height, width, fit, background, position, algorithm, dpr)

Basic Transformations

Parameter	Type	Default
height	integer	N/A
width	integer	N/A
fit	enum: cover, contain, fill, inside, outside	cover
background	color	000000
position	enum: top, bottom, left, right, right_top, right_bottom, left_top, left_bottom, center	center
algorithm	enum: nearest, cubic, mitchell, lanczos2, lanczos3	lanczos3
dpr	float	1

final t = Transformation.tResize(
    height: "",
    width: "",
    fit: "cover",
    background: "000000",
    position: "center",
    algorithm: "lanczos3",
    dpr: "1"
);

2. tCompress(quality)

Basic Transformations

Parameter	Type	Default
quality	integer	80

final t = Transformation.tCompress(
    quality: "80"
);

3. tExtend(top, left, bottom, right, background, borderType, dpr)

Basic Transformations

Parameter	Type	Default
top	integer	10
left	integer	10
bottom	integer	10
right	integer	10
background	color	000000
borderType	enum: constant, replicate, reflect, wrap	constant
dpr	float	1

final t = Transformation.tExtend(
    top: "10",
    left: "10",
    bottom: "10",
    right: "10",
    background: "000000",
    borderType: "constant",
    dpr: "1"
);

4. tExtract(top, left, height, width, boundingBox)

Basic Transformations

Parameter	Type	Default
top	integer	10
left	integer	10
height	integer	50
width	integer	20
boundingBox	bbox	N/A

final t = Transformation.tExtract(
    top: "10",
    left: "10",
    height: "50",
    width: "20",
    boundingBox: ""
);

5. tTrim(threshold)

Basic Transformations

Parameter	Type	Default
threshold	integer	10

final t = Transformation.tTrim(
    threshold: "10"
);

6. tRotate(angle, background)

Basic Transformations

Parameter	Type	Default
angle	integer	N/A
background	color	000000

final t = Transformation.tRotate(
    angle: "",
    background: "000000"
);

7. tFlip()

Basic Transformations

final t = Transformation.tFlip(
);

8. tFlop()

Basic Transformations

final t = Transformation.tFlop(
);

9. tSharpen(sigma)

Basic Transformations

Parameter	Type	Default
sigma	float	1.5

final t = Transformation.tSharpen(
    sigma: "1.5"
);

10. tMedian(size)

Basic Transformations

Parameter	Type	Default
size	integer	3

final t = Transformation.tMedian(
    size: "3"
);

11. tBlur(sigma, dpr)

Basic Transformations

Parameter	Type	Default
sigma	float	0.3
dpr	float	1

final t = Transformation.tBlur(
    sigma: "0.3",
    dpr: "1"
);

12. tFlatten(background)

Basic Transformations

Parameter	Type	Default
background	color	000000

final t = Transformation.tFlatten(
    background: "000000"
);

13. tNegate()

Basic Transformations

final t = Transformation.tNegate(
);

14. tNormalise()

Basic Transformations

final t = Transformation.tNormalise(
);

15. tLinear(a, b)

Basic Transformations

Parameter	Type	Default
a	integer	1
b	integer	N/A

final t = Transformation.tLinear(
    a: "1",
    b: ""
);

16. tModulate(brightness, saturation, hue)

Basic Transformations

Parameter	Type	Default
brightness	float	1
saturation	float	1
hue	integer	90

final t = Transformation.tModulate(
    brightness: "1",
    saturation: "1",
    hue: "90"
);

17. tGrey()

Basic Transformations

final t = Transformation.tGrey(
);

18. tTint(color)

Basic Transformations

Parameter	Type	Default
color	color	000000

final t = Transformation.tTint(
    color: "000000"
);

19. tToformat(format, quality)

Basic Transformations

Parameter	Type	Default
format	enum: jpeg, png, webp, tiff, avif, bmp, heif	jpeg
quality	enum: 100, 95, 90, 85, 80, 75, 70, 60, 50, 40, 30, 20, 10, best, good, eco, low	75

final t = Transformation.tToformat(
    format: "jpeg",
    quality: "75"
);

20. tDensity(density)

Basic Transformations

Parameter	Type	Default
density	integer	300

final t = Transformation.tDensity(
    density: "300"
);

21. tMerge(mode, image, transformation, background, height, width, top, left, gravity, blend, tile, listOfBboxes, listOfPolygons)

Basic Transformations

Parameter	Type	Default
mode	enum: overlay, underlay, wrap	overlay
image	file	N/A
transformation	custom	N/A
background	color	00000000
height	integer	N/A
width	integer	N/A
top	integer	N/A
left	integer	N/A
gravity	enum: northwest, north, northeast, east, center, west, southwest, south, southeast, custom	center
blend	enum: over, in, out, atop, dest, dest-over, dest-in, dest-out, dest-atop, xor, add, saturate, multiply, screen, overlay, darken, lighten, colour-dodge, color-dodge, colour-burn, color-burn, hard-light, soft-light, difference, exclusion	over
tile	boolean	N/A
listOfBboxes	bboxList	N/A
listOfPolygons	polygonList	N/A

final t = Transformation.tMerge(
    mode: "overlay",
    image: "",
    transformation: "",
    background: "00000000",
    height: "",
    width: "",
    top: "",
    left: "",
    gravity: "center",
    blend: "over",
    tile: "",
    listOfBboxes: "",
    listOfPolygons: ""
);

Artifact

1. afRemove()

Artifact Removal Plugin

final t = Transformation.afRemove(
);

AWSRekognitionPlugin

1. awsrekDetectlabels(maximumLabels, minimumConfidence)

Detect objects and text in images

Parameter	Type	Default
maximumLabels	integer	5
minimumConfidence	integer	55

final t = Transformation.awsrekDetectlabels(
    maximumLabels: "5",
    minimumConfidence: "55"
);

2. awsrekModeration(minimumConfidence)

Detect objects and text in images

Parameter	Type	Default
minimumConfidence	integer	55

final t = Transformation.awsrekModeration(
    minimumConfidence: "55"
);

BackgroundGenerator

1. generateBg(backgroundPrompt, focus, negativePrompt, seed)

AI Background Generator

Parameter	Type	Default
backgroundPrompt	custom	YSBmb3Jlc3QgZnVsbCBvZiBvYWsgdHJlZXMsd2l0aCBicmlnaHQgbGlnaHRzLCBzdW4gYW5kIGEgbG90IG9mIG1hZ2ljLCB1bHRyYSByZWFsaXN0aWMsIDhr
focus	enum: Product, Background	Product
negativePrompt	custom	N/A
seed	integer	123

final t = Transformation.generateBg(
    backgroundPrompt: "YSBmb3Jlc3QgZnVsbCBvZiBvYWsgdHJlZXMsd2l0aCBicmlnaHQgbGlnaHRzLCBzdW4gYW5kIGEgbG90IG9mIG1hZ2ljLCB1bHRyYSByZWFsaXN0aWMsIDhr",
    focus: "Product",
    negativePrompt: "",
    seed: "123"
);

ImageExtender

1. bgExtend(boundingBox, prompt, negativePrompt, strength, guidanceScale, numberOfInferenceSteps, colorAdjust, seed)

AI Image Extender

Parameter	Type	Default
boundingBox	bbox	N/A
prompt	custom	N/A
negativePrompt	custom	N/A
strength	float	0.999
guidanceScale	integer	8
numberOfInferenceSteps	integer	10
colorAdjust	boolean	N/A
seed	integer	123

final t = Transformation.bgExtend(
    boundingBox: "",
    prompt: "",
    negativePrompt: "",
    strength: "0.999",
    guidanceScale: "8",
    numberOfInferenceSteps: "10",
    colorAdjust: "",
    seed: "123"
);

VariationGenerator

1. vgGenerate(generateVariationPrompt, noOfVariations, seed, autoscale)

AI Variation Generator

Parameter	Type	Default
generateVariationPrompt	custom	N/A
noOfVariations	integer	1
seed	integer	N/A
autoscale	boolean	true

final t = Transformation.vgGenerate(
    generateVariationPrompt: "",
    noOfVariations: "1",
    seed: "",
    autoscale: "true"
);

EraseBG

1. eraseBg(industryType, addShadow, refine)

EraseBG Background Removal Module

Parameter	Type	Default
industryType	enum: general, ecommerce, car, human, object	general
addShadow	boolean	N/A
refine	boolean	true

final t = Transformation.eraseBg(
    industryType: "general",
    addShadow: "",
    refine: "true"
);

GoogleVisionPlugin

1. googlevisDetectlabels(maximumLabels)

Detect content and text in images

Parameter	Type	Default
maximumLabels	integer	5

final t = Transformation.googlevisDetectlabels(
    maximumLabels: "5"
);

ImageCentering

1. imcDetect(distancePercentage)

Image Centering Module

Parameter	Type	Default
distancePercentage	integer	10

final t = Transformation.imcDetect(
    distancePercentage: "10"
);

IntelligentCrop

1. icCrop(requiredWidth, requiredHeight, paddingPercentage, maintainOriginalAspect, aspectRatio, gravityTowards, preferredDirection, objectType)

Intelligent Crop Plugin

Parameter	Type	Default
requiredWidth	integer	N/A
requiredHeight	integer	N/A
paddingPercentage	integer	N/A
maintainOriginalAspect	boolean	N/A
aspectRatio	string	N/A
gravityTowards	enum: object, foreground, face, none	none
preferredDirection	enum: north_west, north, north_east, west, center, east, south_west, south, south_east	center
objectType	enum: airplane, apple, backpack, banana, baseball_bat, baseball_glove, bear, bed, bench, bicycle, bird, boat, book, bottle, bowl, broccoli, bus, cake, car, carrot, cat, cell_phone, chair, clock, couch, cow, cup, dining_table, dog, donut, elephant, fire_hydrant, fork, frisbee, giraffe, hair_drier, handbag, horse, hot_dog, keyboard, kite, knife, laptop, microwave, motorcycle, mouse, orange, oven, parking_meter, person, pizza, potted_plant, refrigerator, remote, sandwich, scissors, sheep, sink, skateboard, skis, snowboard, spoon, sports_ball, stop_sign, suitcase, surfboard, teddy_bear, tennis_racket, tie, toaster, toilet, toothbrush, traffic_light, train, truck, tv, umbrella, vase, wine_glass, zebra	person

final t = Transformation.icCrop(
    requiredWidth: "",
    requiredHeight: "",
    paddingPercentage: "",
    maintainOriginalAspect: "",
    aspectRatio: "",
    gravityTowards: "none",
    preferredDirection: "center",
    objectType: "person"
);

IntelligentMasking

1. imMask(replacementImage, detector, maskType)

Intelligent Masking

Parameter	Type	Default
replacementImage	file	N/A
detector	enum: face, text, number_plate	number_plate
maskType	enum: fill_black, pixelate, blur	fill_black

final t = Transformation.imMask(
    replacementImage: "",
    detector: "number_plate",
    maskType: "fill_black"
);

ObjectCounter

1. ocDetect()

Classifies whether objects in the image are single or multiple

final t = Transformation.ocDetect(
);

NSFWDetection

1. nsfwDetect(minimumConfidence)

Detect NSFW content in images

Parameter	Type	Default
minimumConfidence	float	0.5

final t = Transformation.nsfwDetect(
    minimumConfidence: "0.5"
);

NumberPlateDetection

1. numplateDetect()

Number Plate Detection Plugin

final t = Transformation.numplateDetect(
);

ObjectDetection

1. odDetect()

Detect bounding boxes of objects in the image

final t = Transformation.odDetect(
);

CheckObjectSize

1. cosDetect(objectThresholdPercent)

Calculates the percentage of the main object area relative to image dimensions.

Parameter	Type	Default
objectThresholdPercent	integer	50

final t = Transformation.cosDetect(
    objectThresholdPercent: "50"
);

TextDetectionandRecognition

1. ocrExtract(detectOnly)

OCR Module

Parameter	Type	Default
detectOnly	boolean	N/A

final t = Transformation.ocrExtract(
    detectOnly: ""
);

PdfWatermarkRemoval

1. pwrRemove()

PDF Watermark Removal Plugin

final t = Transformation.pwrRemove(
);

ProductTagging

1. prTag()

AI Product Tagging

final t = Transformation.prTag(
);

CheckProductVisibility

1. cpvDetect()

Classifies whether the product in the image is completely visible or not

final t = Transformation.cpvDetect(
);

QRCode

1. qrGenerate(width, height, image, margin, qRTypeNumber, qrErrorCorrectionLevel, imageSize, imageMargin, dotsColor, dotsType, dotsBgColor, cornerSquareColor, cornerSquareType, cornerDotsColor, cornerDotsType)

QRCode Plugin

Parameter	Type	Default
width	integer	300
height	integer	300
image	custom	N/A
margin	integer	N/A
qRTypeNumber	integer	N/A
qrErrorCorrectionLevel	enum: L, M, Q, H	Q
imageSize	float	0.4
imageMargin	integer	N/A
dotsColor	color	000000
dotsType	enum: rounded, dots, classy, classy-rounded, square, extra-rounded	square
dotsBgColor	color	ffffff
cornerSquareColor	color	000000
cornerSquareType	enum: dot, square, extra-rounded	square
cornerDotsColor	color	000000
cornerDotsType	enum: dot, square	dot

final t = Transformation.qrGenerate(
    width: "300",
    height: "300",
    image: "",
    margin: "",
    qRTypeNumber: "",
    qrErrorCorrectionLevel: "Q",
    imageSize: "0.4",
    imageMargin: "",
    dotsColor: "000000",
    dotsType: "square",
    dotsBgColor: "ffffff",
    cornerSquareColor: "000000",
    cornerSquareType: "square",
    cornerDotsColor: "000000",
    cornerDotsType: "dot"
);

2. qrScan()

QRCode Plugin

final t = Transformation.qrScan(
);

RemoveBG

1. removeBg()

Remove background from any image

final t = Transformation.removeBg(
);

SoftShadowGenerator

1. shadowGen(backgroundImage, backgroundColor, shadowAngle, shadowIntensity)

AI Soft Shadow Generator

Parameter	Type	Default
backgroundImage	file	N/A
backgroundColor	color	ffffff
shadowAngle	float	120
shadowIntensity	float	0.5

final t = Transformation.shadowGen(
    backgroundImage: "",
    backgroundColor: "ffffff",
    shadowAngle: "120",
    shadowIntensity: "0.5"
);

SuperResolution

1. srUpscale(type, enhanceFace, model, enhanceQuality)

Super Resolution Module

Parameter	Type	Default
type	enum: 2x, 4x, 8x	2x
enhanceFace	boolean	N/A
model	enum: Picasso, Flash	Picasso
enhanceQuality	boolean	N/A

final t = Transformation.srUpscale(
    type: "2x",
    enhanceFace: "",
    model: "Picasso",
    enhanceQuality: ""
);

VertexAI

1. vertexaiGeneratebg(backgroundPrompt, negativePrompt, seed, guidanceScale)

Vertex AI based transformations

Parameter	Type	Default
backgroundPrompt	custom	YSBmb3Jlc3QgZnVsbCBvZiBvYWsgdHJlZXMsd2l0aCBicmlnaHQgbGlnaHRzLCBzdW4gYW5kIGEgbG90IG9mIG1hZ2ljLCB1bHRyYSByZWFsaXN0aWMsIDhr
negativePrompt	custom	N/A
seed	integer	22
guidanceScale	integer	60

final t = Transformation.vertexaiGeneratebg(
    backgroundPrompt: "YSBmb3Jlc3QgZnVsbCBvZiBvYWsgdHJlZXMsd2l0aCBicmlnaHQgbGlnaHRzLCBzdW4gYW5kIGEgbG90IG9mIG1hZ2ljLCB1bHRyYSByZWFsaXN0aWMsIDhr",
    negativePrompt: "",
    seed: "22",
    guidanceScale: "60"
);

2. vertexaiRemovebg()

Vertex AI based transformations

final t = Transformation.vertexaiRemovebg(
);

3. vertexaiUpscale(type)

Vertex AI based transformations

Parameter	Type	Default
type	enum: x2, x4	x2

final t = Transformation.vertexaiUpscale(
    type: "x2"
);

VideoWatermarkRemoval

1. wmvRemove()

Video Watermark Removal Plugin

final t = Transformation.wmvRemove(
);

VideoUpscalerPlugin

1. vsrUpscale()

Video Upscaler Plugin

final t = Transformation.vsrUpscale(
);

ViewDetection

1. vdDetect()

Classifies wear type and view type of products in the image

final t = Transformation.vdDetect(
);

WatermarkRemoval

1. wmRemove(removeText, removeLogo, box1, box2, box3, box4, box5)

Watermark Removal Plugin

Parameter	Type	Default
removeText	boolean	N/A
removeLogo	boolean	N/A
box1	string	0_0_100_100
box2	string	0_0_0_0
box3	string	0_0_0_0
box4	string	0_0_0_0
box5	string	0_0_0_0

final t = Transformation.wmRemove(
    removeText: "",
    removeLogo: "",
    box1: "0_0_100_100",
    box2: "0_0_0_0",
    box3: "0_0_0_0",
    box4: "0_0_0_0",
    box5: "0_0_0_0"
);

WatermarkDetection

1. wmcDetect(detectText)

Watermark Detection Plugin

Parameter	Type	Default
detectText	boolean	N/A

final t = Transformation.wmcDetect(
    detectText: ""
);