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fix modify README.md

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jtc
2022-10-20 10:28:31 +08:00
parent 8241e24abf
commit 040817914a
3 changed files with 23 additions and 31 deletions
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4
AluminumDefectDetection/eval_pre.py
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@@ -19,7 +19,7 @@ import glob
import cv2 import cv2
from StreamManagerApi import StreamManagerApi, MxDataInput from StreamManagerApi import StreamManagerApi, MxDataInput
import numpy as np import numpy as np
from utils import preprocess, scale_coords, xyxy2xywh, is_legal from utils import preproc, scale_coords, xyxy2xywh, is_legal
from plots import box_label, colors from plots import box_label, colors
names = ['non_conduct', 'abrasion_mark', 'corner_leak', 'orange_peel', 'leak', 'jet_flow', 'paint_bubble', 'pit', names = ['non_conduct', 'abrasion_mark', 'corner_leak', 'orange_peel', 'leak', 'jet_flow', 'paint_bubble', 'pit',
@@ -77,7 +77,7 @@ if __name__ == '__main__':
r = 640 / max(h0, w0) # ratio r = 640 / max(h0, w0) # ratio
input_shape = (640, 640) input_shape = (640, 640)
pre_img = preprocess(ori_img, input_shape)[0] pre_img = preproc(ori_img, input_shape)[0]
pre_img = np.ascontiguousarray(pre_img) pre_img = np.ascontiguousarray(pre_img)
pre_img_path = PRE_IMG_PATH + item pre_img_path = PRE_IMG_PATH + item

4
AluminumDefectDetection/main.py
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@@ -18,7 +18,7 @@ import cv2
from StreamManagerApi import StreamManagerApi, MxDataInput from StreamManagerApi import StreamManagerApi, MxDataInput
import numpy as np import numpy as np
from plots import box_label, colors from plots import box_label, colors
from utils import preprocess, scale_coords, xyxy2xywh, is_legal from utils import scale_coords, xyxy2xywh, is_legal, preproc
names = ['non_conduct', 'abrasion_mark', 'corner_leak', 'orange_peel', 'leak', 'jet_flow', 'paint_bubble', 'pit', names = ['non_conduct', 'abrasion_mark', 'corner_leak', 'orange_peel', 'leak', 'jet_flow', 'paint_bubble', 'pit',
'motley', 'dirty_spot'] 'motley', 'dirty_spot']
@@ -49,7 +49,7 @@ if __name__ == '__main__':
r = 640 / max(h0, w0) # ratio r = 640 / max(h0, w0) # ratio
input_shape = (640, 640) input_shape = (640, 640)
pre_img = preprocess(ori_img, input_shape)[0] pre_img = preproc(ori_img, input_shape)[0]
pre_img = np.ascontiguousarray(pre_img) pre_img = np.ascontiguousarray(pre_img)
PRE_IMG_PATH = "pre_" + ORI_IMG_PATH PRE_IMG_PATH = "pre_" + ORI_IMG_PATH
cv2.imwrite(PRE_IMG_PATH, pre_img) cv2.imwrite(PRE_IMG_PATH, pre_img)

46
AluminumDefectDetection/utils.py
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@@ -16,30 +16,26 @@ import os
import numpy as np import numpy as np
import cv2 import cv2
GRAY = 114
def preprocess(im, new_shape, color=(114, 114, 114)):
# Resize and pad image while meeting stride-multiple constraints
shape = im.shape[:2] # current shape [height, width]
if isinstance(new_shape, int):
new_shape = (new_shape, new_shape)
# Scale ratio (new / old) def preproc(img, img_size, swap=(2, 0, 1)):
r = min(new_shape[0] / shape[0], new_shape[1] / shape[1]) """Resize the input image."""
if len(img.shape) == 3:
padding_image = np.ones((img_size[0], img_size[1], 3), dtype=np.uint8) * GRAY
else:
padding_image = np.ones(img_size, dtype=np.uint8) * GRAY
# Compute padding ratio = min(img_size[0] / img.shape[0], img_size[1] / img.shape[1])
ratio = r, r # width, height ratios resized_img = cv2.resize(
new_unpad = int(round(shape[1] * r)), int(round(shape[0] * r)) img,
dw, dh = new_shape[1] - new_unpad[0], new_shape[0] - new_unpad[1] # wh padding (int(img.shape[1] * ratio), int(img.shape[0] * ratio)),
interpolation=cv2.INTER_AREA,
).astype(np.uint8)
top = int((int(img.shape[1] * ratio) - int(img.shape[0] * ratio)) / 2)
padding_image[top: top + int(img.shape[0] * ratio), :int(img.shape[1] * ratio)] = resized_img
dw /= 2 # divide padding into 2 sides return padding_image, ratio
dh /= 2
if shape[::-1] != new_unpad: # resize
im = cv2.resize(im, new_unpad, interpolation=cv2.INTER_AREA)
top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1))
left, right = int(round(dw - 0.1)), int(round(dw + 0.1))
im = cv2.copyMakeBorder(im, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color) # add border
return im, ratio, (dw, dh)
def clip_coords(boxes, shape): def clip_coords(boxes, shape):
@@ -48,13 +44,9 @@ def clip_coords(boxes, shape):
def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None): def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None):
# Rescale coords (xyxy) from img1_shape to img0_shape
if ratio_pad is None: # calculate from img0_shape gain = min(img1_shape[0] / img0_shape[0], img1_shape[1] / img0_shape[1]) # gain = old / new
gain = min(img1_shape[0] / img0_shape[0], img1_shape[1] / img0_shape[1]) # gain = old / new pad = (img1_shape[1] - img0_shape[1] * gain) / 2, (img1_shape[0] - img0_shape[0] * gain) / 2 # wh padding
pad = (img1_shape[1] - img0_shape[1] * gain) / 2, (img1_shape[0] - img0_shape[0] * gain) / 2 # wh padding
else:
gain = ratio_pad[0][0]
pad = ratio_pad[1]
coords[0] -= pad[0] # x padding coords[0] -= pad[0] # x padding
coords[2] -= pad[0] # x padding coords[2] -= pad[0] # x padding