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import numpy as np
# pip install insightface==0.7.3
from insightface.app import FaceAnalysis
import os
import folder_paths
###
# https://github.com/cubiq/ComfyUI_IPAdapter_plus/issues/165#issue-2055829543
###
class FaceAnalysis2(FaceAnalysis):
# def __init__(self, provider="CPU", name="buffalo_l"):
# self.face_analysis = FaceAnalysis(name=name, root=INSIGHTFACE_DIR, providers=[provider + 'ExecutionProvider',])
# self.face_analysis.prepare(ctx_id=0, det_size=(640, 640))
# self.thresholds = THRESHOLDS["ArcFace"]
# NOTE: allows setting det_size for each detection call.
# the model allows it but the wrapping code from insightface
# doesn't show it, and people end up loading duplicate models
# for different sizes where there is absolutely no need to
def get(self, img, max_num=0, det_size=(640, 640)):
if det_size is not None:
self.det_model.input_size = det_size
return super().get(img, max_num)
def analyze_faces(face_analysis: FaceAnalysis, img_data: np.ndarray, det_size=(640, 640)):
# NOTE: try detect faces, if no faces detected, lower det_size until it does
detection_sizes = [None] + [(size, size) for size in range(640, 256, -64)] + [(256, 256)]
for size in detection_sizes:
faces = face_analysis.get(img_data, det_size=size)
if len(faces) > 0:
return faces
return []
def insightface_loader(provider):
try:
from insightface.app import FaceAnalysis
except ImportError as e:
raise Exception(e)
path = os.path.join(folder_paths.models_dir, "insightface")
model = FaceAnalysis(name="buffalo_l", root=path, providers=[provider + 'ExecutionProvider',])
model.prepare(ctx_id=0, det_size=(640, 640))
return model
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