我正在使用tensorflow异物检测API来检测护照上的MRZ代码。我已经训练了数据，并且一切正常。它用边界框完美地标识了包围它的MRZ代码。但是，现在我只想裁剪MRZ代码（或边界框），并且在使用PIL图像库时遇到麻烦。这是我的代码的样子：
# Import packages
import os
import cv2
import numpy as np
import tensorflow as tf
import sys
from PIL import Image
# This is needed since the notebook is stored in the object_detection folder.
sys.path.append("..")
# Import utilites
from utils import label_map_util
from utils import visualization_utils as vis_util
# Name of the directory containing the object detection module we're using
MODEL_NAME = 'inference_graph'
IMAGE_NAME = 'test.jpg'
# Grab path to current working directory
CWD_PATH = os.getcwd()
# Path to frozen detection graph .pb file, which contains the model that is used
# for object detection.
PATH_TO_CKPT = os.path.join(CWD_PATH,MODEL_NAME,'frozen_inference_graph.pb')
# Path to label map file
PATH_TO_LABELS = os.path.join(CWD_PATH,'training','labelmap.pbtxt')
# Path to image
PATH_TO_IMAGE = os.path.join(CWD_PATH,IMAGE_NAME)
# Number of classes the object detector can identify
NUM_CLASSES = 6
# Load the label map.
# Label maps map indices to category names, so that when our convolution
# network predicts `5`, we know that this corresponds to `king`.
# Here we use internal utility functions, but anything that returns a
# dictionary mapping integers to appropriate string labels would be fine
label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES, use_display_name=True)
category_index = label_map_util.create_category_index(categories)
# Load the Tensorflow model into memory.
detection_graph = tf.Graph()
with detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(od_graph_def, name='')
sess = tf.Session(graph=detection_graph)
# Define input and output tensors (i.e. data) for the object detection classifier
# Input tensor is the image
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
# Output tensors are the detection boxes, scores, and classes
# Each box represents a part of the image where a particular object was detected
detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
# Each score represents level of confidence for each of the objects.
# The score is shown on the result image, together with the class label.
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
# Number of objects detected
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
# Load image using OpenCV and
# expand image dimensions to have shape: [1, None, None, 3]
# i.e. a single-column array, where each item in the column has the pixel RGB value
image = cv2.imread(PATH_TO_IMAGE)
image_expanded = np.expand_dims(image, axis=0)
# Perform the actual detection by running the model with the image as input
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_classes, num_detections],
feed_dict={image_tensor: image_expanded})
# Draw the results of the detection (aka 'visulaize the results')
vis_util.visualize_boxes_and_labels_on_image_array(
image,
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8,
min_score_thresh=0.80)
width, height = image.shape[:2]
for i, box in enumerate(np.squeeze(boxes)):
if(np.squeeze(scores)[i] > 0.80):
(ymin, xmin, ymax, xmax) = (box[0]*height, box[1]*width, box[2]*height, box[3]*width)
im = Image.open('test.jpg')
im.crop((ymin, xmin, ymax - ymax, xmax - xmin)).show()
# All the results have been drawn on image. Now display the image.
cv2.imshow('Object detector', image)
# Press any key to close the image
cv2.waitKey(0)
# Clean up
cv2.destroyAllWindows()
However, I always get the following error:
Traceback (most recent call last):
File "/usr/local/lib/python3.6/site-packages/PIL/ImageFile.py", line 482, in _save
fh = fp.fileno()
AttributeError: '_idat' object has no attribute 'fileno'
在处理上述异常期间，发生了另一个异常：
Traceback (most recent call last):
File "object_detection_image.py", line 128, in <module>
im.crop((ymin, xmin, ymax - ymax, xmax - xmin)).show()
File "/usr/local/lib/python3.6/site-packages/PIL/Image.py", line 1977, in show
_show(self, title=title, command=command)
File "/usr/local/lib/python3.6/site-packages/PIL/Image.py", line 2802, in _show
_showxv(image, **options)
File "/usr/local/lib/python3.6/site-packages/PIL/Image.py", line 2807, in _showxv
ImageShow.show(image, title, **options)
File "/usr/local/lib/python3.6/site-packages/PIL/ImageShow.py", line 51, in show
if viewer.show(image, title=title, **options):
File "/usr/local/lib/python3.6/site-packages/PIL/ImageShow.py", line 75, in show
return self.show_image(image, **options)
File "/usr/local/lib/python3.6/site-packages/PIL/ImageShow.py", line 95, in show_image
return self.show_file(self.save_image(image), **options)
File "/usr/local/lib/python3.6/site-packages/PIL/ImageShow.py", line 91, in save_image
return image._dump(format=self.get_format(image), **self.options)
File "/usr/local/lib/python3.6/site-packages/PIL/Image.py", line 624, in _dump
self.save(filename, format, **options)
File "/usr/local/lib/python3.6/site-packages/PIL/Image.py", line 1930, in save
save_handler(self, fp, filename)
File "/usr/local/lib/python3.6/site-packages/PIL/PngImagePlugin.py", line 821, in _save
[("zip", (0, 0)+im.size, 0, rawmode)])
File "/usr/local/lib/python3.6/site-packages/PIL/ImageFile.py", line 490, in _save
e.setimage(im.im, b)
SystemError: tile cannot extend outside image
我尝试过多次更改数字。有时裁剪的图片只是黑色的。试图搜索谷歌，但似乎无法获得边界框。非常感谢您的帮助。
答案 0 :(得分：0)
您需要做的就是在指定的路径模型/ research / object detection / utils / visualizatioin.py中找到文件
做以下事情
import cv2
count = 0
找到功能
def draw_bounding_box_on_image():
draw = ImageDraw.Draw(image):
arr = numpy.array(image)
im_width, im_height = image.size
if use_normalized_coordinates:
(left, right, top, bottom) = (xmin * im_width, xmax * im_width,
ymin * im_height, ymax * im_height)
a,b,c,d = int(left) , int(right) , int(top) ,int(bottom)
arr = arr[c:d,a:b]
cv2.imwrite("yourpath/QRCODE{}.jpg".format(count),arr)
count = count+1
else:
(left, right, top, bottom) = (xmin, xmax, ymin, ymax)
draw.line([(left, top), (left, bottom), (right, bottom),
(right, top), (left, top)], width=thickness, fill=color
答案 1 :(得分：0)
我在visualization_utils.py的最后添加了以下代码，
找到函数'visualize_boxes_and_labels_on_image_array' 然后将检测到的框附加到数组中。
for i in range(min(max_boxes_to_draw, boxes.shape[0])):
if scores is None or scores[i] > min_score_thresh:
box = tuple(boxes[i].tolist())
bigger_bounding_box.append(box)
我添加了以下代码：
bigger_bounding_box=[]
count =0
for i in range(0,len(bigger_bounding_box)):
im_width, im_height = image.shape[0], image.shape[1]
arr = numpy.array(image)
box = bigger_bounding_box[i]
xmin = box[0]
ymin = box[1]
xmax = box[2]
ymax = box[3]
(left, right, top, bottom) = (xmin * im_width, xmax * im_width, ymin * im_height, ymax * im_height)
a,b,c,d = int(left) , int(right) , int(top) ,int(bottom)
arr = arr[c:d,a:b]
cv2.imwrite("C:/Users/tensor19/Desktop/images/QRCODE{}.jpg".format(count),arr)
count =count+1
该模型能够检测输入图像中的对象，但无法裁剪与输入图像中检测到的对象相同的对象。