Как я могу получить выход YOLO в самом ноутбуке Jupyter? - PullRequest
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Как я могу получить выход YOLO в самом ноутбуке Jupyter?

0 голосов
/ 06 апреля 2019

Я хочу запустить YOLO с предварительно обученной моделью, используя darkflow на ноутбуке jupyter. Я позаботился об импорте и выдаче видеовхода с предварительно подготовленными весами.Когда мы выполняем локально, мы обычно получаем специальное окно, которое показывает выходное видео с выходом YOLO, но как мне получить это окно вывода видео прямо в блокноте. 

import cv2
from darkflow.net.build import TFNet
import numpy as np
import time
from IPython.display import clear_output, Image, display, HTML
import base64

option = {
    'model': 'cfg/yolo.cfg',
    'load': 'bin/yolo.weights',
    'threshold': 0.2,
    'gpu': 0.0
}

tfnet = TFNet(options)

capture = cv2.VideoCapture('football.mp4')
colors = [tuple(255 * np.random.rand(3)) for i in range(5)]

def arrayShow (imageArray):
    ret, png = cv2.imencode('.png', imageArray)
    encoded = base64.b64encode(png)
    return Image(data=encoded.decode('ascii'))

while (capture.isOpened()):
    stime = time.time()
    ret, frame = capture.read()
    if ret:
        results = tfnet.return_predict(frame)
        for color, result in zip(colors, results):
            tl = (result['topleft']['x'], result['topleft']['y'])
            br = (result['bottomright']['x'], result['bottomright']['y'])
            label = result['label']
            frame = cv2.rectangle(frame, tl, br, color, 7)
            frame = cv2.putText(frame, label, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
        cv2.imshow('frame', frame)
        print('FPS {:.1f}'.format(1 / (time.time() - stime)))
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    else:
        capture.release()
        cv2.destroyAllWindows()
        break

Я получил следующий результат, который кажется правильным(я новичок в opencv и YOLO) 

Parsing ./cfg/yolo.cfg
Parsing cfg/yolo.cfg
Loading bin/yolo.weights ...
Successfully identified 203934260 bytes
Finished in 0.09525442123413086s
Model has a coco model name, loading coco labels.

Building net ...
Source | Train? | Layer description                | Output size
-------+--------+----------------------------------+---------------
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
       |        | input                            | (?, 608, 608, 3)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 608, 608, 32)
 Load  |  Yep!  | maxp 2x2p0_2                     | (?, 304, 304, 32)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 304, 304, 64)
 Load  |  Yep!  | maxp 2x2p0_2                     | (?, 152, 152, 64)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 152, 152, 128)
 Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 152, 152, 64)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 152, 152, 128)
 Load  |  Yep!  | maxp 2x2p0_2                     | (?, 76, 76, 128)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 76, 76, 256)
 Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 76, 76, 128)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 76, 76, 256)
 Load  |  Yep!  | maxp 2x2p0_2                     | (?, 38, 38, 256)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 38, 38, 512)
 Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 38, 38, 256)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 38, 38, 512)
 Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 38, 38, 256)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 38, 38, 512)
 Load  |  Yep!  | maxp 2x2p0_2                     | (?, 19, 19, 512)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)
 Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 19, 19, 512)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)
 Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 19, 19, 512)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)
 Load  |  Yep!  | concat [16]                      | (?, 38, 38, 512)
 Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 38, 38, 64)
 Load  |  Yep!  | local flatten 2x2                | (?, 19, 19, 256)
 Load  |  Yep!  | concat [27, 24]                  | (?, 19, 19, 1280)
 Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)
 Load  |  Yep!  | conv 1x1p0_1    linear           | (?, 19, 19, 425)
-------+--------+----------------------------------+---------------
Running entirely on CPU
Finished in 5.595241069793701s

НО после этого я не получил никакого вывода видео

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