238 lines
9.5 KiB
Python
238 lines
9.5 KiB
Python
import numpy as np
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import cv2
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from PIL import Image
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from .utils import str2bool, str2int
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from ctypes import c_float
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from .Runner_base import Runner_base, Param_base
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class General(Param_base):
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type = 'bilinear'
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keep_ratio = True
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zoom = True
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calculate_ratio_using_CSim = True
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resize_w = 0
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resize_h = 0
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resized_w = 0
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resized_h = 0
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def update(self, **dic):
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self.type = dic['type']
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self.keep_ratio = str2bool(dic['keep_ratio'])
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self.zoom = str2bool(dic['zoom'])
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self.calculate_ratio_using_CSim = str2bool(dic['calculate_ratio_using_CSim'])
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self.resize_w = str2int(dic['resize_w'])
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self.resize_h = str2int(dic['resize_h'])
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def __str__(self):
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str_out = [
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', type:',str(self.type),
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', keep_ratio:',str(self.keep_ratio),
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', zoom:',str(self.zoom),
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', calculate_ratio_using_CSim:',str(self.calculate_ratio_using_CSim),
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', resize_w:',str(self.resize_w),
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', resize_h:',str(self.resize_h),
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', resized_w:',str(self.resized_w),
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', resized_h:',str(self.resized_h)]
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return(' '.join(str_out))
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class Hw(Param_base):
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resize_bit = 12
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def update(self, **dic):
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pass
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def __str__(self):
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str_out = [
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', resize_bit:',str(self.resize_bit)]
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return(' '.join(str_out))
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class runner(Runner_base):
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## overwrite the class in Runner_base
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general = General()
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hw = Hw()
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def __str__(self):
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return('<Resize>')
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def update(self, **kwargs):
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super().update(**kwargs)
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## if resize size has not been assigned, then it will take model size as resize size
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if self.general.resize_w == 0 or self.general.resize_h == 0:
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self.general.resize_w = self.common.model_size[0]
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self.general.resize_h = self.common.model_size[1]
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assert(self.general.resize_w > 0)
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assert(self.general.resize_h > 0)
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##
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if self.common.numerical_type == '520':
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self.general.type = 'fixed_520'
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elif self.common.numerical_type == '720':
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self.general.type = 'fixed_720'
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assert(self.general.type.lower() in ['BILINEAR', 'Bilinear', 'bilinear', 'BICUBIC', 'Bicubic', 'bicubic', 'FIXED', 'Fixed', 'fixed', 'FIXED_520', 'Fixed_520', 'fixed_520', 'FIXED_720', 'Fixed_720', 'fixed_720','CV', 'cv', 'opencv', 'OpenCV', 'CV2', 'cv2'])
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def run(self, image_data):
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## init
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ori_w = image_data.shape[1]
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ori_h = image_data.shape[0]
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info = {}
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##
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if self.general.keep_ratio:
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self.general.resized_w, self.general.resized_h = self.calcuate_scale_keep_ratio(self.general.resize_w,self.general.resize_h, ori_w, ori_h, self.general.calculate_ratio_using_CSim)
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else:
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self.general.resized_w = int(self.general.resize_w)
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self.general.resized_h = int(self.general.resize_h)
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assert(self.general.resized_w > 0)
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assert(self.general.resized_h > 0)
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##
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if (self.general.resized_w > ori_w) or (self.general.resized_h > ori_h):
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if not self.general.zoom:
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info['size'] = (ori_w,ori_h)
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if str2bool(self.common.print_info):
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print('no resize')
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self.print_info()
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return image_data, info
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## resize
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if self.general.type.lower() in ['BILINEAR', 'Bilinear', 'bilinear']:
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image_data = self.do_resize_bilinear(image_data, self.general.resized_w, self.general.resized_h)
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elif self.general.type.lower() in ['BICUBIC', 'Bicubic', 'bicubic']:
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image_data = self.do_resize_bicubic(image_data, self.general.resized_w, self.general.resized_h)
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elif self.general.type.lower() in ['CV', 'cv', 'opencv', 'OpenCV', 'CV2', 'cv2']:
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image_data = self.do_resize_cv2(image_data, self.general.resized_w, self.general.resized_h)
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elif self.general.type.lower() in ['FIXED', 'Fixed', 'fixed', 'FIXED_520', 'Fixed_520', 'fixed_520', 'FIXED_720', 'Fixed_720', 'fixed_720']:
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image_data = self.do_resize_fixed(image_data, self.general.resized_w, self.general.resized_h, self.hw.resize_bit, self.general.type)
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# output
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info['size'] = (self.general.resized_w, self.general.resized_h)
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# print info
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if str2bool(self.common.print_info):
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self.print_info()
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return image_data, info
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def calcuate_scale_keep_ratio(self, tar_w, tar_h, ori_w, ori_h, calculate_ratio_using_CSim):
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if not calculate_ratio_using_CSim:
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scale_w = tar_w * 1.0 / ori_w*1.0
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scale_h = tar_h * 1.0 / ori_h*1.0
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scale = scale_w if scale_w < scale_h else scale_h
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new_w = int(round(ori_w * scale))
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new_h = int(round(ori_h * scale))
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return new_w, new_h
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## calculate_ratio_using_CSim
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scale_w = c_float(tar_w * 1.0 / (ori_w * 1.0)).value
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scale_h = c_float(tar_h * 1.0 / (ori_h * 1.0)).value
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scale_ratio = 0.0
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scale_target_w = 0
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scale_target_h = 0
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padH = 0
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padW = 0
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bScaleW = True if scale_w < scale_h else False
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if bScaleW:
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scale_ratio = scale_w
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scale_target_w = int(c_float(scale_ratio * ori_w + 0.5).value)
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scale_target_h = int(c_float(scale_ratio * ori_h + 0.5).value)
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assert (abs(scale_target_w - tar_w) <= 1), "Error: scale down width cannot meet expectation\n"
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padH = tar_h - scale_target_h
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padW = 0
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assert (padH >= 0), "Error: padH shouldn't be less than zero\n"
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else:
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scale_ratio = scale_h
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scale_target_w = int(c_float(scale_ratio * ori_w + 0.5).value)
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scale_target_h = int(c_float(scale_ratio * ori_h + 0.5).value)
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assert (abs(scale_target_h - tar_h) <= 1), "Error: scale down height cannot meet expectation\n"
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padW = tar_w - scale_target_w
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padH = 0
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assert (padW >= 0), "Error: padW shouldn't be less than zero\n"
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new_w = tar_w - padW
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new_h = tar_h - padH
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return new_w, new_h
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def do_resize_bilinear(self, image_data, resized_w, resized_h):
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img = Image.fromarray(image_data)
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img = img.resize((resized_w, resized_h), Image.BILINEAR)
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image_data = np.array(img).astype('uint8')
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return image_data
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def do_resize_bicubic(self, image_data, resized_w, resized_h):
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img = Image.fromarray(image_data)
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img = img.resize((resized_w, resized_h), Image.BICUBIC)
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image_data = np.array(img).astype('uint8')
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return image_data
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def do_resize_cv2(self, image_data, resized_w, resized_h):
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image_data = cv2.resize(image_data, (resized_w, resized_h))
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image_data = np.array(image_data)
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# image_data = np.array(image_data).astype('uint8')
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return image_data
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def do_resize_fixed(self, image_data, resized_w, resized_h, resize_bit, type):
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if len(image_data.shape) < 3:
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m, n = image_data.shape
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tmp = np.zeros((m,n,3), dtype=np.uint8)
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tmp[:,:,0] = image_data
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image_data = tmp
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c = 3
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gray = True
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else:
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m, n, c = image_data.shape
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gray = False
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resolution = 1 << resize_bit
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# Width
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ratio = int(((n - 1) << resize_bit) / (resized_w - 1))
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ratio_cnt = 0
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src_x = 0
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resized_image_w = np.zeros((m, resized_w, c), dtype=np.uint8)
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for dst_x in range(resized_w):
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while ratio_cnt > resolution:
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ratio_cnt = ratio_cnt - resolution
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src_x = src_x + 1
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mul1 = np.ones((m, c)) * (resolution - ratio_cnt)
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mul2 = np.ones((m, c)) * ratio_cnt
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resized_image_w[:, dst_x, :] = np.multiply(np.multiply(
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image_data[:, src_x, :], mul1) + np.multiply(image_data[:, src_x + 1, :], mul2), 1/resolution)
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ratio_cnt = ratio_cnt + ratio
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# Height
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ratio = int(((m - 1) << resize_bit) / (resized_h - 1))
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## NPU HW special case 2 , only on 520
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if type.lower() in ['FIXED_520', 'Fixed_520', 'fixed_520']:
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if (((ratio * (resized_h - 1)) % 4096 == 0) and ratio != 4096):
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ratio -= 1
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ratio_cnt = 0
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src_x = 0
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resized_image = np.zeros(
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(resized_h, resized_w, c), dtype=np.uint8)
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for dst_x in range(resized_h):
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while ratio_cnt > resolution:
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ratio_cnt = ratio_cnt - resolution
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src_x = src_x + 1
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mul1 = np.ones((resized_w, c)) * (resolution - ratio_cnt)
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mul2 = np.ones((resized_w, c)) * ratio_cnt
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## NPU HW special case 1 , both on 520 / 720
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if (((dst_x > 0) and ratio_cnt == resolution) and (ratio != resolution)):
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if type.lower() in ['FIXED_520', 'Fixed_520', 'fixed_520','FIXED_720', 'Fixed_720', 'fixed_720' ]:
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resized_image[dst_x, :, :] = np.multiply(np.multiply(
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resized_image_w[src_x+1, :, :], mul1) + np.multiply(resized_image_w[src_x + 2, :, :], mul2), 1/resolution)
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else:
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resized_image[dst_x, :, :] = np.multiply(np.multiply(
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resized_image_w[src_x, :, :], mul1) + np.multiply(resized_image_w[src_x + 1, :, :], mul2), 1/resolution)
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ratio_cnt = ratio_cnt + ratio
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if gray:
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resized_image = resized_image[:,:,0]
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return resized_image
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