|
|
|
|
|
import cv2 |
|
import numpy as np |
|
from PIL import Image |
|
|
|
from ..util import HWC3, resize_image |
|
|
|
|
|
class LineartStandardDetector: |
|
def __call__( |
|
self, |
|
input_image=None, |
|
guassian_sigma=6.0, |
|
intensity_threshold=8, |
|
detect_resolution=512, |
|
output_type="pil", |
|
): |
|
if not isinstance(input_image, np.ndarray): |
|
input_image = np.array(input_image, dtype=np.uint8) |
|
else: |
|
output_type = output_type or "np" |
|
|
|
original_height, original_width, _ = input_image.shape |
|
|
|
input_image = HWC3(input_image) |
|
input_image = resize_image(input_image, detect_resolution) |
|
|
|
x = input_image.astype(np.float32) |
|
g = cv2.GaussianBlur(x, (0, 0), guassian_sigma) |
|
intensity = np.min(g - x, axis=2).clip(0, 255) |
|
intensity /= max(16, np.median(intensity[intensity > intensity_threshold])) |
|
intensity *= 127 |
|
detected_map = intensity.clip(0, 255).astype(np.uint8) |
|
|
|
detected_map = HWC3(detected_map) |
|
|
|
detected_map = cv2.resize( |
|
detected_map, |
|
(original_width, original_height), |
|
interpolation=cv2.INTER_CUBIC, |
|
) |
|
|
|
if output_type == "pil": |
|
detected_map = Image.fromarray(detected_map) |
|
|
|
return detected_map |
|
|
