download better face detection module dynamically (54f0c148) · Commits · github_fork / Stable Diffusion Webui

modules/textual_inversion/autocrop.py

+20 −0

Original line number	Diff line number	Diff line
		import cv2
		import requests
		import os
		from collections import defaultdict
		from math import log, sqrt
		@@ -293,6 +294,25 @@ def is_square(w, h):
		return w == h


		def download_and_cache_models(dirname):
		download_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true'
		model_file_name = 'face_detection_yunet.onnx'

		if not os.path.exists(dirname):
		os.makedirs(dirname)

		cache_file = os.path.join(dirname, model_file_name)
		if not os.path.exists(cache_file):
		print(f"downloading face detection model from '{download_url}' to '{cache_file}'")
		response = requests.get(download_url)
		with open(cache_file, "wb") as f:
		f.write(response.content)

		if os.path.exists(cache_file):
		return cache_file
		return None


		class PointOfInterest:
		def __init__(self, x, y, weight=1.0, size=10):
		self.x = x

+11 −2

Original line number	Diff line number	Diff line
		@@ -7,6 +7,7 @@ import tqdm
		import time

		from modules import shared, images
		from modules.paths import models_path
		from modules.shared import opts, cmd_opts
		from modules.textual_inversion import autocrop
		if cmd_opts.deepdanbooru:
		@@ -146,14 +147,22 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
		save_pic(splitted, index, existing_caption=existing_caption)
		process_default_resize = False

		if process_entropy_focus and img.height != img.width:
		if process_focal_crop and img.height != img.width:

		dnn_model_path = None
		try:
		dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv"))
		except Exception as e:
		print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e)

		autocrop_settings = autocrop.Settings(
		crop_width = width,
		crop_height = height,
		face_points_weight = process_focal_crop_face_weight,
		entropy_points_weight = process_focal_crop_entropy_weight,
		corner_points_weight = process_focal_crop_edges_weight,
		annotate_image = process_focal_crop_debug
		annotate_image = process_focal_crop_debug,
		dnn_model_path = dnn_model_path,
		)
		for focal in autocrop.crop_image(img, autocrop_settings):
		save_pic(focal, index, existing_caption=existing_caption)

+2 −0