cudanexus/detic 🖼️❓📝 → ❓
About
Detecting Twenty-thousand Classes using Image-level Supervision
Example Output
Output
{"image":"https://replicate.delivery/pbxt/8Z3ePZdM4YQGCCENdN8egqBDXAsCDPRIkczkeKA6QntNtwLkA/out.png","jsona":"https://replicate.delivery/pbxt/1tYTuPjeYO2nVS0Ll1hDIMIc2524f3oDAUlNb9E9pWbnW4FSA/output.json"}
Performance Metrics
2.60s
Prediction Time
120.88s
Total Time
All Input Parameters
{
"image": "https://replicate.delivery/pbxt/K6zgH3un6xi4l07DFSUOgHKzOIbWktlvmc348VZbRDqSbqeV/k67kjlB.jpeg",
"vocabulary": "lvis",
"custom_vocabulary": "None"
}
Input Parameters
- image (required)
- input image
- vocabulary
- Choose vocabulary
- custom_vocabulary (required)
- Type your own vocabularies, separated by coma ','
Output Schema
- image
- Image
- jsona
- Jsona
Example Execution Logs
Resetting zs_weight datasets/metadata/lvis_v1_clip_a+cname.npy JSON data written to /tmp/tmpe847452h/output.json
Version Details
- Version ID
64998fbfaa64b44ef350920eeb18c8db1cda7dbcea9945e3996fefda407815bf- Version Created
- January 3, 2024