質問編集履歴
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CentOSの仮想環境でmatplotlibが表示されないguest: host: windows10
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CentOSの仮想環境でmatplotlibが表示されないguest: centos7 host: windows10
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見づらかったのでコメントを削除しました
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else:
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e = TfPoseEstimator(get_graph_path(args.model), target_size=(w, h))
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image = common.read_imgfile(args.image, None, None)
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if image is None:
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logger.error('Image can not be read, path=%s' % args.image)
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bgimg = cv2.cvtColor(image.astype(np.uint8), cv2.COLOR_BGR2RGB)
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bgimg = cv2.resize(bgimg, (e.heatMat.shape[1], e.heatMat.shape[0]), interpolation=cv2.INTER_AREA)
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# show network output
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a = fig.add_subplot(2, 2, 2)
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plt.imshow(bgimg, alpha=0.5)
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tmp = np.amax(e.heatMat[:, :, :-1], axis=2)
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a = fig.add_subplot(2, 2, 3)
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a.set_title('Vectormap-x')
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plt.imshow(tmp2_odd, cmap=plt.cm.gray, alpha=0.5)
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plt.colorbar()
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a = fig.add_subplot(2, 2, 4)
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a.set_title('Vectormap-y')
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plt.imshow(tmp2_even, cmap=plt.cm.gray, alpha=0.5)
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plt.colorbar()
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plt.show()
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run.py のコードを入れなおしました。宜しくお願いします。
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[vagrant@localhost tf-pose-estimation]$ python3 run.py
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--model=mobilenet_thin --resize=432x368 --image=images/p2.jpg
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/home/vagrant/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1)
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or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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_np_qint8 = np.dtype([("qint8", np.int8, 1)])
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/home/vagrant/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1)
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or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
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/home/vagrant/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1)
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・
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・
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TfPoseEstimator/Openpose/MConv_Stage6_L2_5_pointwise/BatchNorm/FusedBatchNorm
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TfPoseEstimator/Openpose/concat_stage7/axis
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----------------------------------
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WARNING:tensorflow:From /home/vagrant/tf-pose-estimation/tf_pose/estimator.py:341: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
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import argparse
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import logging
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import sys
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import time
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from tf_pose import common
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import cv2
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import numpy as np
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from tf_pose.estimator import TfPoseEstimator
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from tf_pose.networks import get_graph_path, model_wh
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logger = logging.getLogger('TfPoseEstimatorRun')
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logger.handlers.clear()
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logger.setLevel(logging.DEBUG)
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ch = logging.StreamHandler()
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ch.setLevel(logging.DEBUG)
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formatter = logging.Formatter('[%(asctime)s] [%(name)s] [%(levelname)s] %(message)s')
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ch.setFormatter(formatter)
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logger.addHandler(ch)
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WARNING:tensorflow:From /home/vagrant/tf-pose-estimation/tf_pose/tensblur/smoother.py:96: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='tf-pose-estimation run')
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parser.add_argument('--image', type=str, default='./images/p1.jpg')
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parser.add_argument('--model', type=str, default='cmu',
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help='cmu / mobilenet_thin / mobilenet_v2_large / mobilenet_v2_small')
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parser.add_argument('--resize', type=str, default='0x0',
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help='if provided, resize images before they are processed. '
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'default=0x0, Recommends : 432x368 or 656x368 or 1312x736 ')
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parser.add_argument('--resize-out-ratio', type=float, default=4.0,
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help='if provided, resize heatmaps before they are post-processed. default=1.0')
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args = parser.parse_args()
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w, h = model_wh(args.resize)
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if w == 0 or h == 0:
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e = TfPoseEstimator(get_graph_path(args.model), target_size=(432, 368))
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else:
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e = TfPoseEstimator(get_graph_path(args.model), target_size=(w, h))
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# estimate human poses from a single image !
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image = common.read_imgfile(args.image, None, None)
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if image is None:
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logger.error('Image can not be read, path=%s' % args.image)
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sys.exit(-1)
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t = time.time()
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humans = e.inference(image, resize_to_default=(w > 0 and h > 0), upsample_size=args.resize_out_ratio)
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elapsed = time.time() - t
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logger.info('inference image: %s in %.4f seconds.' % (args.image, elapsed))
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image = TfPoseEstimator.draw_humans(image, humans, imgcopy=False)
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try:
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import matplotlib
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import matplotlib.pyplot as plt
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fig = plt.figure()
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a = fig.add_subplot(2, 2, 1)
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a.set_title('Result')
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plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
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bgimg = cv2.cvtColor(image.astype(np.uint8), cv2.COLOR_BGR2RGB)
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bgimg = cv2.resize(bgimg, (e.heatMat.shape[1], e.heatMat.shape[0]), interpolation=cv2.INTER_AREA)
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# show network output
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a = fig.add_subplot(2, 2, 2)
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plt.imshow(bgimg, alpha=0.5)
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tmp = np.amax(e.heatMat[:, :, :-1], axis=2)
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plt.imshow(tmp, cmap=plt.cm.gray, alpha=0.5)
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plt.colorbar()
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tmp2 = e.pafMat.transpose((2, 0, 1))
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tmp2_odd = np.amax(np.absolute(tmp2[::2, :, :]), axis=0)
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tmp2_even = np.amax(np.absolute(tmp2[1::2, :, :]), axis=0)
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a = fig.add_subplot(2, 2, 3)
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a.set_title('Vectormap-x')
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# plt.imshow(CocoPose.get_bgimg(inp, target_size=(vectmap.shape[1], vectmap.shape[0])), alpha=0.5)
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plt.imshow(tmp2_odd, cmap=plt.cm.gray, alpha=0.5)
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plt.colorbar()
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a = fig.add_subplot(2, 2, 4)
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a.set_title('Vectormap-y')
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# plt.imshow(CocoPose.get_bgimg(inp, target_size=(vectmap.shape[1], vectmap.shape[0])), alpha=0.5)
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plt.imshow(tmp2_even, cmap=plt.cm.gray, alpha=0.5)
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plt.colorbar()
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plt.show()
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except Exception as e:
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logger.warning('matplotlib error, %s' % e)
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cv2.imshow('result', image)
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cv2.waitKey()
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-----------------------------------------------
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