CEFAS24-111 Contract for marine litter image annotation services on Ocean Country Partnership Programme (OCPP)
key details
| Value | £100,000 |
|---|---|
| Status | complete |
| Category (CPV) | 72316000 |
| Deadline | 20 Sept 2024 |
| Contract start | 16 Dec 2024 |
| Contract end | 31 Mar 2025 |
| Procedure | open |
| SME suitable | Yes |
| OCID | ocds-b5fd17-c74a426b-2d05-41d5-82da-e2d5f38270fc |
Award
| Supplier | Value | Date | Status |
|---|---|---|---|
| Envision | £47,933 | 16 Dec 2024 | active |
description
The Ocean Country Partnership Programme (OCPP) is funded through official development assistance (ODA) as part of the UK's £500 million Blue Planet Fund. Through the OCPP, the UK government partners with ODA-eligible countries to deliver tangible and positive impacts on the livelihoods of coastal communities that depend on healthy marine ecosystems. The programme supports countries to strengthen marine science expertise, develop science-based policy and management tools, and create educational resources for coastal communities.
Cefas require the Supplier to provide a marine litter annotation service on drone survey images of beaches for OCPP partners countries. These annotations will be used by Cefas and partners to train machine learning algorithm to automatically detect litter, analyse and report on marine litter. However, the high heterogeneity of litter items within classes (e.g. plastic drinking bottles), sometimes subtle differences between classes (plastic drinking bottles vs plastic cleaning bottles) and regional differences in litter generated (e.g. plastic drinking bags vs plastic drinking bottles) underline the need for large numbers of quality assured annotation data.
The Supplier will provide in-country partners with introductory training on the processes, business models and training needed to establish effective image annotation processes.
notice history
1 notice published against this procurement.
| Published | Type | Regime | Notice |
|---|---|---|---|
| 10 Mar 2025 | Award (award) | · | 07c68948-4503-411f-87f4-fde9dc38ae3a-832681 |
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source
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