Python `TypeError:类型为'的对象；非类型'；在jupyter笔记本上运行基本M RCNN程序时没有len（）`错误

我正在运行一个基本的maskr cnn程序来检测物体。它正在使用coco数据集。我正在连接到AWS Ec2实例的Jupyter笔记本上运行此程序。我发现以下错误

Below is the traceback from this internal error.

Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 3343, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-1-dfbb133297e0>", line 117, in <module>
    cv2.imshow('frame', frame)
cv2.error: OpenCV(4.2.0) /home/ubuntu/src/opencv/modules/highgui/src/window.cpp:651: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function 'cvShowImage'


During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2044, in showtraceback
    stb = value._render_traceback_()
AttributeError: 'error' object has no attribute '_render_traceback_'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py", line 1169, in get_records
    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py", line 316, in wrapped
    return f(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py", line 350, in _fixed_getinnerframes
    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))
  File "/usr/lib/python3.6/inspect.py", line 1490, in getinnerframes
    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)
  File "/usr/lib/python3.6/inspect.py", line 1448, in getframeinfo
    filename = getsourcefile(frame) or getfile(frame)
  File "/usr/lib/python3.6/inspect.py", line 696, in getsourcefile
    if getattr(getmodule(object, filename), '__loader__', None) is not None:
  File "/usr/lib/python3.6/inspect.py", line 733, in getmodule
    if ismodule(module) and hasattr(module, '__file__'):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/__init__.py", line 50, in __getattr__
    module = self._load()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/__init__.py", line 44, in _load
    module = _importlib.import_module(self.__name__)
  File "/usr/lib/python3.6/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 994, in _gcd_import
  File "<frozen importlib._bootstrap>", line 971, in _find_and_load
  File "<frozen importlib._bootstrap>", line 955, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 665, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 678, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/contrib/__init__.py", line 48, in <module>
    from tensorflow.contrib import estimator
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/contrib/estimator/__init__.py", line 30, in <module>
    from tensorflow_estimator.contrib import estimator
ModuleNotFoundError: No module named 'tensorflow_estimator.contrib'
---------------------------------------------------------------------------
error                                     Traceback (most recent call last)
    [... skipping hidden 1 frame]

<ipython-input-1-dfbb133297e0> in <module>
    116 
--> 117     cv2.imshow('frame', frame)
    118     cv2.waitkey(0)

error: OpenCV(4.2.0) /home/ubuntu/src/opencv/modules/highgui/src/window.cpp:651: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function 'cvShowImage'


During handling of the above exception, another exception occurred:

AttributeError                            Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py in showtraceback(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)
   2043                         # in the engines. This should return a list of strings.
-> 2044                         stb = value._render_traceback_()
   2045                     except Exception:

AttributeError: 'error' object has no attribute '_render_traceback_'

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
    [... skipping hidden 1 frame]

/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py in showtraceback(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)
   2045                     except Exception:
   2046                         stb = self.InteractiveTB.structured_traceback(etype,
-> 2047                                             value, tb, tb_offset=tb_offset)
   2048 
   2049                     self._showtraceback(etype, value, stb)

/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py in structured_traceback(self, etype, value, tb, tb_offset, number_of_lines_of_context)
   1434             self.tb = tb
   1435         return FormattedTB.structured_traceback(
-> 1436             self, etype, value, tb, tb_offset, number_of_lines_of_context)
   1437 
   1438 

/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py in structured_traceback(self, etype, value, tb, tb_offset, number_of_lines_of_context)
   1334             # Verbose modes need a full traceback
   1335             return VerboseTB.structured_traceback(
-> 1336                 self, etype, value, tb, tb_offset, number_of_lines_of_context
   1337             )
   1338         elif mode == 'Minimal':

/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py in structured_traceback(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)
   1191 
   1192         formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,
-> 1193                                                                tb_offset)
   1194 
   1195         colors = self.Colors  # just a shorthand + quicker name lookup

/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py in format_exception_as_a_whole(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)
   1148 
   1149 
-> 1150         last_unique, recursion_repeat = find_recursion(orig_etype, evalue, records)
   1151 
   1152         frames = self.format_records(records, last_unique, recursion_repeat)

/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py in find_recursion(etype, value, records)
    449     # first frame (from in to out) that looks different.
    450     if not is_recursion_error(etype, value, records):
--> 451         return len(records), 0
    452 
    453     # Select filename, lineno, func_name to track frames with

TypeError: object of type 'NoneType' has no len()

---

尝试安装它

pip安装-U tensorflow\U估计器

。或者阅读。

import numpy as np
import tensorflow

print(tensorflow.__version__)

def random_colors(N):
    np.random.seed(1)
    colors = [tuple(255 * np.random.rand(3)) for _ in range(N)]
    return colors


def apply_mask(image, mask, color, alpha=0.5):
    """apply mask to image"""
    for n, c in enumerate(color):
        image[:, :, n] = np.where(
            mask == 1,
            image[:, :, n] * (1 - alpha) + alpha * c,
            image[:, :, n]
        )
    return image


def display_instances(image, boxes, masks, ids, names, scores):
    """
        take the image and results and apply the mask, box, and Label
    """
    n_instances = boxes.shape[0]
    colors = random_colors(n_instances)

    if not n_instances:
        print('NO INSTANCES TO DISPLAY')
    else:
        assert boxes.shape[0] == masks.shape[-1] == ids.shape[0]

    for i, color in enumerate(colors):
        if not np.any(boxes[i]):
            continue

        y1, x1, y2, x2 = boxes[i]
        label = names[ids[i]]
        score = scores[i] if scores is not None else None
        caption = '{} {:.2f}'.format(label, score) if score else label
        mask = masks[:, :, i]

        image = apply_mask(image, mask, color)
        image = cv2.rectangle(image, (x1, y1), (x2, y2), color, 2)
        image = cv2.putText(
            image, caption, (x1, y1), cv2.FONT_HERSHEY_COMPLEX, 0.7, color, 2
        )

    return image


if __name__ == '__main__':
    """
        test everything
    """
    import os
    import sys

    from mrcnn import utils
    from mrcnn import model as modellib

    ROOT_DIR = os.getcwd()
    MODEL_DIR = os.path.join(ROOT_DIR, "logs")
    COCO_MODEL_PATH = os.path.join(ROOT_DIR, "mask_rcnn_coco.h5")
    if not os.path.exists(COCO_MODEL_PATH):
        utils.download_trained_weights(COCO_MODEL_PATH)

    sys.path.append(os.path.join(ROOT_DIR, "samples/coco/"))  # To find local version
    import coco

    class InferenceConfig(coco.CocoConfig):
        GPU_COUNT = 1
        IMAGES_PER_GPU = 1

    config = InferenceConfig()
    config.display()

    model = modellib.MaskRCNN(
        mode="inference", model_dir=MODEL_DIR, config=config
    )
    model.load_weights(COCO_MODEL_PATH, by_name=True)
    class_names = [
        'BG', 'person', 'bicycle', 'car', 'motorcycle', 'airplane',
        'bus', 'train', 'truck', 'boat', 'traffic light',
        'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird',
        'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear',
        'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie',
        'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball',
        'kite', 'baseball bat', 'baseball glove', 'skateboard',
        'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup',
        'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
        'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza',
        'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed',
        'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote',
        'keyboard', 'cell phone', 'microwave', 'oven', 'toaster',
        'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors',
        'teddy bear', 'hair drier', 'toothbrush'
    ]

    #capture = cv2.VideoCapture(0)

    # these 2 lines can be removed if you dont have a 1080p camera.
    ##capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
    #capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)

    #while True:
    frame = cv2.imread("test_images.jpg")
    results = model.detect([frame], verbose=0)
    r = results[0]
    frame = display_instances(
        frame, r['rois'], r['masks'], r['class_ids'], class_names, r['scores']
    )

    cv2.imshow('frame', frame)
    cv2.waitkey(0)
    #if cv2.waitKey(1) & 0xFF == ord('q'):
     #      break
    #capture.release()
    cv2.destroyAllWindows()