CMLO
CMLO

Version: 11.11.0b (2024-05-14)

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CMLO by SciDrones

ACTIVE UPLOAD ID: none
none
OBJECT INFERENCE FILTER
Result: 
Confidence: (% - %]
Object inference
result
Object inference
confidence
Objects / 100sqm
(litter)
Objects / 100sqm
(litter)
Query results
No results to show...
All user data
ID DATA DATE IMAGE
COUNT
UPLD
GEOM
IMG
FOOTPRINT
MAP
REPORT
DENSITY
MAP
Logged-in user data
ID TITLE DESCRIPTION DATA DATE IMAGE
COUNT
UPLD
GEOM
IMG
FOOTPRINT
MAP
REPORT
DENSITY
MAP
Admin user data
ID USERNAME TITLE DESCRIPTION ENTITY DATA DATE IMAGE
COUNT
UPLD
GEOM
IMG
FOOTPRINT
MAP
REPORT
DENSITY
MAP
Image details
Object inference result
Object density litter count

Basemaps and Layers

Basemaps
Generic upload layers
Upload data layers
Data filtering options
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CMLO | Account page

User registration

First name Last name Email Username Password

Reset password

Email Username

Reset password

Email Username Password
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Edit account.
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CMLO | Upload page

USER DATA UPLOAD TABLE
Upld
status
Upld
id
Upld title Upld description Upld entity Data
date
Drone
make/model
Data
img info
Data
geom
Data
alt band (m)
Upld ts Img footprint
(map page)
Upld report
(map page)

Fields "Data date", "Drone make" and "Drone model" are derived from the image EXIF data and are automatically populated.

Maximum length: 32 characters. 32 characters remaining.

Maximum length: 512 characters. 512 characters remaining.

Maximum length: 32 characters. 32 characters remaining.

File maximum size: 3800MB. Allowed file format:

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CMLO | Admin page

UPLOAD OVERVIEW TABLE
Upld
status
Upld
id
Usr
id
Username Upld title Upld description Upld entity Data
date
Drone
make/model
Data
img info
Data
geom
Data
alt band (m)
Upld ts Prep.
log
Prep.
dur (min)
Inference
log
Inference
dur (min)
Img footprint
(map page)
Upld report
(map page)
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CMLO | Application info

Introduction

This web site is part of the Coastal Marine Litter Observatory (CMLO). By using CMLO registered users can upload bespoke drone imagery which is fed into a deep learning algorithm for litter detection. The end result of this process is litter inference information that can be downloaded or viewed on map.

Data usage policy CMLO processes user-uploaded data ("images", "datasets") in order to locate litter and produce litter-related metadata through the use of various AI algorithms. Generally CMLO stores all user and system actions paired with the user id or upload id (when applicable) and relative timestamps. This information is used for administrative reasons. What information does CMLO store when a user registers? - First/Last name - Username/Encrypted password - Email (used for registration or for password reset) - Entity (optional) - User "active" status - Registration timestamp What information does CMLO store when a user logs in/updates session? - User id - Connection token used for two-factor authentication (login) - Session timestamp used for session expiration checks What information does CMLO store when a user uploads a dataset? - User id / (Generated) upload id - Upload-related descriptive data (optional: title, description, entity etc) - Upload-related operation data (UAS make/model, UAS camera make/model, dataset timestamps, dataset footprints/altitudes/yaw, algorithm-related image preparation timestamps) - Raw image data What information does CMLO store when a dataset is inferred by an AI algorithm? - Upload id - Inference timestamps - Tile inference result (litter/no litter) or litter location and class result (when applicable) Uploaded dataset policy Non-logged-in users can view the coverage of every valid dataset uploaded on map, along with dataset image count and generic image timestamp. Logged-in users can retrieve additional data specifically related to their uploads: - Image footprints - Raw images - Inference results (ie tile images/footprints/results, litter locations etc)

CMLO | SciDrones | version 11.11.0b | 2024-05-14 | email: info at scidrones.com

Changelog


		

CMLO by SciDrones

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CMLO | Label page

Mode

Image/Tile loader

Image/Tile functions

Class

Object options

Review objects
    Labeling stats

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