> ## Documentation Index > Fetch the complete documentation index at: https://docs.halfpagetechnologies.com/llms.txt > Use this file to discover all available pages before exploring further. # Delete an image > Permanently delete an image and all of its derived storage (converted TIFF/PNG, thumbnail, and any training artifacts), freeing its slot against your storage cap. Any resumable upload still in flight is aborted first, so its uploaded chunks are released too. Scoped to your organization — an image outside it returns `404`, exactly like the reads. ## OpenAPI ````yaml /api-reference/openapi.json delete /api/v1/upload/{image_id} openapi: 3.1.0 info: title: HalfPage API description: > The **HalfPage API** runs Cellpose-based cell segmentation on your microscopy images programmatically — upload an image, run a prediction, and export the resulting cell masks, ROIs, and measurements. ## Base URL ``` https://api.halfpagetechnologies.com/backend/api/v1 ``` Every path in this reference is relative to that base URL. A staging environment is available at `https://staging-api.halfpagetechnologies.com/backend/api/v1`. ## Authentication Authenticate every request with an API key in the `Authorization` header as a bearer token: ``` Authorization: Bearer hp_live_xxxxxxxxxxxxxxxxxxxxxxxx ``` Create and manage keys from the **API Keys** section of the HalfPage dashboard — keys cannot be minted through the API. A key is scoped to the organization that owns it; every resource you create or read is confined to that organization. Requests without a valid key receive `401`; a valid key used against an endpoint outside the public product surface receives `403`. ## Core workflow Three steps — **upload, predict, export** — plus a model list to choose from. Segmentation runs asynchronously on GPU workers, so step 2 is poll-based: 1. **Upload an image** (`POST /upload`) as `multipart/form-data` with a `file` part. One call: the image record is created for you and the response returns it already `ready`, with the `image.id` for the next step. *(Large file or flaky connection? POST the same endpoint as `application/json` with `{"name": ..., "size": ...}` instead. You get back presigned part URLs — PUT the chunks, call `POST /upload/{image_id}/complete`, then poll `GET /upload/{image_id}` until `upload_status` is `ready`.)* 2. **Pick a model** (`GET /models`) and **run a prediction** (`POST /predict`) with the `image_id` and a `model_id`. That returns a `prediction_id`; poll `GET /predict/{prediction_id}` until `status` is `COMPLETED`. The response then carries a `segmentation_id` and the `cell_count` detected. 3. **Export** that segmentation as CSV measurements (`GET /export/{segmentation_id}/measurements.csv`), GeoJSON ROIs (`.../rois.geojson`), or an ImageJ ROI archive (`.../rois.zip`). ## Quotas Uploads and analyses are metered against your plan. Exceeding your image storage cap or monthly analysis cap returns `402` with a human-readable `detail` explaining the limit — upgrade your plan to raise it. version: 1.0.0 servers: - url: https://api.halfpagetechnologies.com/backend description: Production - url: https://staging-api.halfpagetechnologies.com/backend description: Staging security: [] tags: - name: upload description: >- Get microscopy images into HalfPage, and manage them once they are there. `POST /upload` is the only way in and covers both modes: send `multipart/form-data` with a `file` part to upload in one request (the image comes back `ready`), or send `application/json` with `{name, size}` to open a resumable upload and get presigned part URLs back. Resumable uploads finish with `complete` (no ETag bookkeeping needed) and are polled until `ready`. - name: predict description: >- Run segmentation on a ready image and poll it to completion. `POST /predict` queues the run on a GPU worker and returns a `prediction_id`; `GET /predict/{prediction_id}` reports progress and, once `COMPLETED`, the `segmentation_id` and cell count of the result. - name: export description: >- Download a completed segmentation in analysis-ready formats: a CSV of per-cell measurements, a GeoJSON of ROI polygons, or a ZIP of ImageJ-compatible ROIs. The CSV endpoint accepts a `columns` parameter to narrow the output to the measurements you care about. - name: models description: >- List the segmentation models available to your organization — the shared public base models (e.g. `cpsam`) plus any custom models trained in the dashboard — to choose a `model_id` for a prediction. paths: /api/v1/upload/{image_id}: delete: tags: - upload summary: Delete an image description: >- Permanently delete an image and all of its derived storage (converted TIFF/PNG, thumbnail, and any training artifacts), freeing its slot against your storage cap. Any resumable upload still in flight is aborted first, so its uploaded chunks are released too. Scoped to your organization — an image outside it returns `404`, exactly like the reads. operationId: delete_upload_api_v1_upload__image_id__delete parameters: - name: image_id in: path required: true schema: type: string title: Image Id responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/DeleteUploadResponse' '401': description: >- Missing or invalid credentials. Supply a valid `Authorization: Bearer hp_live_...` API key. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: detail: Requires authentication '404': description: The resource does not exist, or is not in your organization. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: detail: Image with id 3fa85f64-5717-4562-b3fc-2c963f66afa6 not found '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - HTTPBearer: [] components: schemas: DeleteUploadResponse: properties: success: type: boolean title: Success default: true type: object title: DeleteUploadResponse description: Acknowledgement that an image and its derived storage were deleted. ErrorResponse: properties: detail: type: string title: Detail examples: - Job with id 11111111-1111-1111-1111-111111111111 not found type: object required: - detail title: ErrorResponse description: |- The body returned for a handled error: a single human-readable ``detail`` string. HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type input: title: Input ctx: type: object title: Context type: object required: - loc - msg - type title: ValidationError securitySchemes: HTTPBearer: type: http scheme: bearer ````