Developer & DevOps

[2/3] Media preparation (two types) for anomaly detection (crops data set)

48 nodes 196 133 Automatic trigger
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Workflow Description

Advanced workflow for preparing dual-type media data to feed anomaly detection models on crops dataset, integrating manual triggers, HTTP requests, programmatic transformations, data splitting and merging operations.

How it works

  1. 1.Activate workflow manually and receive initial data inputs
  2. 2.Fetch media data from external sources via HTTP requests
  3. 3.Process and transform data programmatically with type-based splitting
  4. 4.Apply custom logic and configure intermediate variables
  5. 5.Merge processed data streams from parallel paths
  6. 6.Prepare final outputs for downstream pipeline consumption

Use cases

  • Prepare images and video datasets for crop anomaly detection models
  • Handle multi-source heterogeneous media data processing in parallel workflows

Requirements

  • Available HTTP endpoints providing required media datasets
  • Data processing and imaging libraries supported in code execution environment

Service Value

Ready-made workflow template for automation delivery and service execution.

Apps Used

Manual Trigger HTTP Request Code Set Split Out Merge Note

Details

Trigger Automatic trigger
Nodes 48
Apps 7
Views 196
Downloads 133

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (48)

/

When clicking ‘Test workflow’

Manual Trigger

#1

Total Points in Collection

HTTP Request

#2

Cluster Distance Matrix

HTTP Request

#3

Scipy Sparse Matrix

Code

#4

Set medoid id

HTTP Request

#5

Get Medoid Vector

HTTP Request

#6

Prepare for Searching Threshold

Set

#7

Searching Score

HTTP Request

#8

Threshold Score

Set

#9

Set medoid threshold score

HTTP Request

#10

Split Out1

Split Out

#11

Merge

Merge

#12

Textual (visual) crop descriptions

Set

#13

Embed text

HTTP Request

#14

Get Medoid by Text

HTTP Request

#15

Set text medoid id

HTTP Request

#16

Prepare for Searching Threshold1

Set

#17

Threshold Score1

Set

#18

Searching Text Medoid Score

HTTP Request

#19

Medoids Variables

Set

#20

Text Medoids Variables

Set

#21

Qdrant cluster variables

Set

#22

Info About Crop Clusters

Set

#23

Crop Counts

HTTP Request

#24

Sticky Note

Sticky Note

#25

Sticky Note1

Sticky Note

#26

Sticky Note2

Sticky Note

#27

Sticky Note3

Sticky Note

#28

Sticky Note4

Sticky Note

#29

Sticky Note5

Sticky Note

#30

Sticky Note6

Sticky Note

#31

Sticky Note8

Sticky Note

#32

Sticky Note9

Sticky Note

#33

Split Out

Split Out

#34

Sticky Note10

Sticky Note

#35

Sticky Note11

Sticky Note

#36

Sticky Note12

Sticky Note

#37

Sticky Note13

Sticky Note

#38

Sticky Note14

Sticky Note

#39

Set text medoid threshold score

HTTP Request

#40

Sticky Note15

Sticky Note

#41

Sticky Note16

Sticky Note

#42

Sticky Note17

Sticky Note

#43

Sticky Note18

Sticky Note

#44

Sticky Note19

Sticky Note

#45

Sticky Note20

Sticky Note

#46

Sticky Note21

Sticky Note

#47

Sticky Note22

Sticky Note

#48

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