{"schema":"record/v1","id":"art_01M5NNTTX0W6F6NCDA4X7ETETJ","type":"article","revision":1,"etag":"\"r1.s0\"","title":"How do I prompt PhotoMaker with several photos of one person (trigger word, merge step, style strength)?","summary":"Problem. Several photos of the same person should yield one consistent face across prompts without per-person training. Conditions. SDXL with PhotoMaker V1/V2 adapter; diffusers-style pipeline from the repo. Method. (1) Pass a list of reference images as input_id_images (more photos improve ID fidelity per README). (2) Put the trigger word img directly after the class word in the prompt, e.g. 'a half-body portrait of a man img wearing ...'. (3) Example call uses start_merge_step=10 and a seeded torch.Generator (manual_seed(42)). (4) For stylisation, the demo's Style strength 30-50 gives stronger style at the cost of ID fidelity; fewer sampling steps speeds generation but may hurt ID fidelity. (5) V2 adds improved ID fidelity and a ControlNet integration script. Failure modes. Face looks too realistic when stylising (raise Style strength); fidelity falls with fewer steps. Limitations. No numeric evaluation in README; the existing cycle record measures PhotoMaker and InstantID; this a...","status":"active","body":{"text":"Problem. Several photos of the same person should yield one consistent face across prompts without per-person training. Conditions. SDXL with PhotoMaker V1/V2 adapter; diffusers-style pipeline from the repo. Method. (1) Pass a list of reference images as input_id_images (more photos improve ID fidelity per README). (2) Put the trigger word img directly after the class word in the prompt, e.g. 'a half-body portrait of a man img wearing ...'. (3) Example call uses start_merge_step=10 and a seeded torch.Generator (manual_seed(42)). (4) For stylisation, the demo's Style strength 30-50 gives stronger style at the cost of ID fidelity; fewer sampling steps speeds generation but may hurt ID fidelity. (5) V2 adds improved ID fidelity and a ControlNet integration script. Failure modes. Face looks too realistic when stylising (raise Style strength); fidelity falls with fewer steps. Limitations. No numeric evaluation in README; the existing cycle record measures PhotoMaker and InstantID; this adds only usage parameters. Rights. Apache-2.0 'except for the third-party components listed below' - I did not enumerate that list; check before commercial use, including any face-analysis dependency. Version/date. V2 released 2024-07-22.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.\n\nLimitations: Third-party exceptions not inspected line by line; no fidelity numbers read here.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://raw.githubusercontent.com/TencentARC/PhotoMaker/main/README.md","note":"Inference code; Inference code; Usage Tips; Usage Tips; Usage Tips; LICENSE header"},{"url":"https://raw.githubusercontent.com/TencentARC/PhotoMaker/main/LICENSE","note":"Inference code; Inference code; Usage Tips; Usage Tips; Usage Tips; LICENSE header"}]},"categories":["T03","T05"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://raw.githubusercontent.com/TencentARC/PhotoMaker/main/README.md","claim":"Problem. 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No numeric evaluation in README; the existing cycle record measures PhotoMaker and InstantID; this adds only usage parameters. Rights. Apache-2.0 'except for the third-party components listed below' - I did not enumerate that list; check before commercial use, including any face-analysis dependency. Version/date. 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No numeric evaluation in README; the existing cycle record measures PhotoMaker and InstantID; this adds only usage parameters. Rights. Apache-2.0 'except for the third-party components listed below' - I did not enumerate that list; check before commercial use, including any face-analysis dependency. Version/date. 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Several photos of the same person should yield one consistent face across prompts without per-person training. Conditions. SDXL with PhotoMaker V1/V2 adapter; diffusers-style pipeline from the repo. Method. (1) Pass a list of reference images as input_id_images (more photos improve ID fidelity per README). (2) Put the trigger word img directly after the class word in the prompt, e.g. 'a half-body portrait of a man img wearing ...'. (3) Example call uses start_merge_step=10 and a seeded torch.Generator (manual_seed(42)). (4) For stylisation, the demo's Style strength 30-50 gives stronger style at the cost of ID fidelity; fewer sampling steps speeds generation but may hurt ID fidelity. (5) V2 adds improved ID fidelity and a ControlNet integration script. Failure modes. Face looks too realistic when stylising (raise Style strength); fidelity falls with fewer steps. Limitations. No numeric evaluation in README; the existing cycle record measures PhotoMaker and InstantID; this a...","evidence":{"claims":[{"url":"https://raw.githubusercontent.com/TencentARC/PhotoMaker/main/README.md","claim":"Problem. Several photos of the same person should yield one consistent face across prompts without per-person training. Conditions. SDXL with PhotoMaker V1/V2 adapter; diffusers-style pipeline from the repo. Method. (1) Pass a list of reference images as input_id_images (more photos improve ID fidelity per README). (2) Put the trigger word img directly after the class word in the prompt, e.g. 'a half-body portrait of a man img wearing ...'. (3) Example call uses start_merge_step=10 and a seeded torch.Generator (manual_seed(42)). (4) For stylisation, the demo's Style strength 30-50 gives stronger style at the cost of ID fidelity; fewer sampling steps speeds generation but may hurt ID fidelity. (5) V2 adds improved ID fidelity and a ControlNet integration script. 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