tfaour
49bc9f9ec9
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Replaces the smart_crop_faces boolean with a 4-way display_mode select on each frame's Configuration tab (image_pipeline.DISPLAY_MODES): - Crop to fill / Crop to faces: the previous False/True behavior, unchanged (center-crop trimming excess, optionally shifted to keep faces on screen). - Stretch to fill (new): fills the panel exactly, aspect ratio not preserved -- a plain resize, no crop. - Shrink to fit (new): the whole photo visible, letterboxed with white where it doesn't fill the panel. Named-face overlay label positioning (face_labels.py, the manage menu's "who's in this photo") now goes through a shared _placement_transform() in image_pipeline.py instead of duplicating crop-box math, so label placement stays correct (and in-bounds) under all four modes, not just the two crop ones -- letterbox/stretch never crop a face out, so labels just use straight scale+offset math there. Schema migration v5 adds display_mode, backfills it from the old boolean (True/False -> crop_faces/crop_fill), and drops the boolean. Verified against the live-shaped test database: the migration (existing frames correctly preserved as crop_faces), the config page's new 4-option select, actual renders under letterbox (confirmed real white letterbox padding in the packed panel-code bytes) and stretch_fill, invalid-input fallback, and the standing legacy-device curl suite.
80 lines
3.4 KiB
Python
80 lines
3.4 KiB
Python
"""Maps named faces (from Immich's own face recognition/People feature)
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onto their position in the final rendered 800x480 frame, for the
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manage-button overlay's escalated "who's in this photo" menu level.
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No face detection or recognition happens here or anywhere else in this
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project -- Immich's GET /api/faces?id={assetId} already returns each
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detected face's bounding box plus a nullable `person` object (with a
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`name`, if the user has identified them in Immich); this module only
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does the coordinate math to place a label next to a *named* one.
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"""
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from __future__ import annotations
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import io
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from PIL import Image, ImageOps
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from .image_pipeline import _placement_transform, logical_render_size, logical_to_native
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# Small caps, not arbitrary: each label is its own malloc'd overlay
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# buffer on the device (see firmware/main/manage_qr_overlay.c), and the
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# four existing fixed corner regions already use a meaningful chunk of
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# the ESP32-C6's limited RAM. Capping at 4 short names keeps the total
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# overlay memory budget well clear of the WiFi/HTTP stack's own needs.
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MAX_LABELED_FACES = 4
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NAME_MAX_LEN = 10
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def compute_face_labels(preview_bytes: bytes, faces: list[dict], display_mode: str,
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orientation: str = "landscape") -> list[dict]:
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"""Returns up to MAX_LABELED_FACES [{"name", "x", "y"}], x/y in native
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800x480 panel pixel space at each named face's bottom-center point.
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Faces without an Immich-identified person name are skipped entirely.
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preview_bytes must be the same preview image render_frame() used for
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the currently-displayed frame, and display_mode/orientation must
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match the settings that were active then -- otherwise the placement
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and rotation computed here won't match what's actually on screen.
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The placement math runs in logical (pre-rotation) space, matching
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render_frame()'s composition step (see image_pipeline._placement_transform,
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shared so the two can't drift apart); each anchor is then rotated
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into native panel coordinates via logical_to_native(), since the
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firmware draws labels in native space.
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"""
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named = [face for face in faces if (face.get("person") or {}).get("name")]
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if not named:
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return []
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logical_w, logical_h = logical_render_size(orientation)
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fitted = ImageOps.exif_transpose(Image.open(io.BytesIO(preview_bytes)).convert("RGB"))
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scale_x, scale_y, offset_x, offset_y = _placement_transform(
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fitted.width, fitted.height, logical_w, logical_h, display_mode, faces
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)
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labels = []
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for face in named[:MAX_LABELED_FACES]:
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face_w = face.get("imageWidth") or fitted.width
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face_h = face.get("imageHeight") or fitted.height
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img_scale_x = fitted.width / face_w
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img_scale_y = fitted.height / face_h
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center_x = (face["boundingBoxX1"] + face["boundingBoxX2"]) / 2 * img_scale_x
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bottom_y = face["boundingBoxY2"] * img_scale_y
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frame_x = center_x * scale_x + offset_x
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frame_y = bottom_y * scale_y + offset_y
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if not (0 <= frame_x <= logical_w and 0 <= frame_y <= logical_h):
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continue # this face got cropped out of the final frame entirely
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name = face["person"]["name"]
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if len(name) > NAME_MAX_LEN:
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name = name[: NAME_MAX_LEN - 3] + "..."
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native_x, native_y = logical_to_native(frame_x, frame_y, orientation)
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labels.append({"name": name, "x": native_x, "y": native_y})
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return labels
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