Documentation Index Fetch the complete documentation index at: https://docs.oxen.ai/llms.txt
Use this file to discover all available pages before exploring further.
Try Topaz Image Upscaler in the Workbench Run this model interactively, tune parameters, and compare outputs.
Model ID: topazlabs-image-upscaleProfessional-grade image upscaling powered by AI, from Topaz Labs.
Standard V2 (general purpose) Low Resolution V2 (for low-res images) CGI (for digital art) High Fidelity V2 (preserves details) Text Refine (optimized for text)
Example request Use the Workbench as a request builder: configure parameters for this model in the UI, then open the API tab to copy the exact cURL or Python call. Sync
Async
Async with SSE
See the image editing reference for more details. curl -X POST https://hub.oxen.ai/api/ai/images/edit \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $OXEN_API_KEY " \ -d '{ "model": "topazlabs-image-upscale", "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png" }'
curl -X POST https://hub.oxen.ai/api/ai/images/edit \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $OXEN_API_KEY " \ -d '{ "model": "topazlabs-image-upscale", "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png", "enhance_model": "High Fidelity V2", "upscale_factor": "2x", "output_format": "png" }'
See the async queue reference for more details. # Enqueue, capture the generation id. GEN_ID = $( curl -s -X POST https://hub.oxen.ai/api/ai/queue \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $OXEN_API_KEY " \ -d '{ "model": "topazlabs-image-upscale", "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png" }' | jq -r '.generations[0].generation_id' ) # Poll until the generation reaches a terminal status. while true ; do STATUS = $( curl -s -H "Authorization: Bearer $OXEN_API_KEY " \ "https://hub.oxen.ai/api/ai/queue/ $GEN_ID " | jq -r '.status' ) echo "Status: $STATUS " case $STATUS in succeeded | failed | cancelled ) break ;; esac sleep 5 done # Print the result. curl -s -H "Authorization: Bearer $OXEN_API_KEY " \ "https://hub.oxen.ai/api/ai/queue/ $GEN_ID " | jq .
# Enqueue, capture the generation id. GEN_ID = $( curl -s -X POST https://hub.oxen.ai/api/ai/queue \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $OXEN_API_KEY " \ -d '{ "model": "topazlabs-image-upscale", "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png", "enhance_model": "High Fidelity V2", "upscale_factor": "2x", "output_format": "png" }' | jq -r '.generations[0].generation_id' ) # Poll until the generation reaches a terminal status. while true ; do STATUS = $( curl -s -H "Authorization: Bearer $OXEN_API_KEY " \ "https://hub.oxen.ai/api/ai/queue/ $GEN_ID " | jq -r '.status' ) echo "Status: $STATUS " case $STATUS in succeeded | failed | cancelled ) break ;; esac sleep 5 done # Print the result. curl -s -H "Authorization: Bearer $OXEN_API_KEY " \ "https://hub.oxen.ai/api/ai/queue/ $GEN_ID " | jq .
See the async queue reference for more details. # Enqueue, capture the generation id. GEN_ID = $( curl -s -X POST https://hub.oxen.ai/api/ai/queue \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $OXEN_API_KEY " \ -d '{ "model": "topazlabs-image-upscale", "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png" }' | jq -r '.generations[0].generation_id' ) # Stream the SSE channel, grab the data line that follows a # media_generation_completed event for our id, and pretty-print it. curl -sN -H "Authorization: Bearer $OXEN_API_KEY " https://hub.oxen.ai/api/events \ | awk -v id=" $GEN_ID " ' /^event: media_generation_completed$/ { expect=1; next } /^data: / && expect { payload = substr($0, 7) if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit } expect = 0 } ' | jq .
# Enqueue, capture the generation id. GEN_ID = $( curl -s -X POST https://hub.oxen.ai/api/ai/queue \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $OXEN_API_KEY " \ -d '{ "model": "topazlabs-image-upscale", "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png", "enhance_model": "High Fidelity V2", "upscale_factor": "2x", "output_format": "png" }' | jq -r '.generations[0].generation_id' ) # Stream the SSE channel, grab the data line that follows a # media_generation_completed event for our id, and pretty-print it. curl -sN -H "Authorization: Bearer $OXEN_API_KEY " https://hub.oxen.ai/api/events \ | awk -v id=" $GEN_ID " ' /^event: media_generation_completed$/ { expect=1; next } /^data: / && expect { payload = substr($0, 7) if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit } expect = 0 } ' | jq .
Fetch model details The models endpoint returns the full model object, including its json_request_schema.
curl -H "Authorization: Bearer $OXEN_API_KEY " https://hub.oxen.ai/api/ai/models/topazlabs-image-upscale
Request parameters Required parameters Field Type Default Description input_imagestring"https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"Image to use as reference. Must be jpeg, png, gif, or webp. Format: uri.
Optional parameters Field Type Default Description enhance_modelstring"High Fidelity V2"Models to Use: Standard V2 (general purpose), Low Resolution V2 (for low-res images), CGI (for digital art), High Fidelity V2 (preserves details), Text Refine (optimized for text) One of: Standard V2, Low Resolution V2, CGI, High Fidelity V2, Text Refine. upscale_factorstring"2x"How much to upscale the image One of: 4x, 2x. output_formatstring"png"Format of the output images One of: jpg, png.
