구름IDE 파이썬,tensorflow 이미지 바로 볼수 있는 창 문의


  • Level 3

    지금 tensorflow 에서 Object detection 보고 따라 하고 있는데 코랩에서 하는 거는 바로바로 이미지가 뜨는데 구름IDE로 하려면 작업이 안되거나(죽었다 라고표시됨) 되더라도 결과값을 확인이 안됩니다. ```

    code_text

    For running inference on the TF-Hub module.

    import tensorflow as tf

    import tensorflow_hub as hub

    For downloading the image.

    import matplotlib.pyplot as plt
    import tempfile
    from six.moves.urllib.request import urlopen
    from six import BytesIO

    For drawing onto the image.

    import numpy as np
    from PIL import Image
    from PIL import ImageColor
    from PIL import ImageDraw
    from PIL import ImageFont
    from PIL import ImageOps

    For measuring the inference time.

    import time

    Print Tensorflow version

    print(tf.version)

    Check available GPU devices.

    print("The following GPU are available: %s" % tf.test.gpu_device_name())

    def display_image(image):
    # fig = plt.figure(figsize=(20, 15))
    plt.grid(False)
    plt.imshow(image)

    def download_and_resize_image(url, new_width=256, new_height=256,
    display=False):
    _, filename = tempfile.mkstemp(suffix=".jpg")
    response = urlopen(url)
    image_data = response.read()
    image_data = BytesIO(image_data)
    pil_image = Image.open(image_data)
    pil_image = ImageOps.fit(pil_image, (new_width, new_height),
    Image.ANTIALIAS)
    pil_image_rgb = pil_image.convert("RGB")
    pil_image_rgb.save(filename, format="JPEG", quality=90)
    print("Image downloaded to %s." % filename)
    if display:
    display_image(pil_image)
    return filename

    def draw_bounding_box_on_image(image,
    ymin,
    xmin,
    ymax,
    xmax,
    color,
    font,
    thickness=4,
    display_str_list=()):
    """Adds a bounding box to an image."""
    draw = ImageDraw.Draw(image)
    im_width, im_height = image.size
    (left, right, top, bottom) = (xmin * im_width, xmax * im_width,
    ymin * im_height, ymax * im_height)
    draw.line([(left, top), (left, bottom), (right, bottom), (right, top),
    (left, top)], width=thickness, fill=color)

    # If the total height of the display strings added to the top of the boundi
    # box exceeds the top of the image, stack the strings below the bounding bo
    # instead of above.
    
    display_str_heights = [font.getsize(ds)[1] for ds in display_str_list]
    # Each display_str has a top and bottom margin of 0.05x.
    total_display_str_height = (1 + 2 * 0.05) * sum(display_str_heights)
    
    if top > total_display_str_height:
        text_bottom = top
    else:
        text_bottom = top + total_display_str_height
        # Reverse list and print from bottom to top.
    for display_str in display_str_list[::-1]:
        text_width, text_height = font.getsize(display_str)
        margin = np.ceil(0.05 * text_height)
        draw.rectangle([(left, text_bottom - text_height - 2 * margin),
                        (left + text_width, text_bottom)],
                       fill=color)
        draw.text((left + margin, text_bottom - text_height - margin),
                  display_str,
                  fill="black",
                  font=font)
        text_bottom -= text_height - 2 * margin
    

    def draw_boxes(image, boxes, class_names, scores, max_boxes=10, min_score=0.1):
    """Overlay labeled boxes on an image with formatted scores and label names
    ."""
    colors = list(ImageColor.colormap.values())

    try:
        font = ImageFont.truetype("/usr/share/fonts/truetype/liberation/Libera\
    

    tionSansNarrow-Regular.ttf", 25)
    except IOError:
    print("Font not found, using default font.")
    font = ImageFont.load_default()

    for i in range(min(boxes.shape[0], max_boxes)):
        if scores[i] >= min_score:
            ymin, xmin, ymax, xmax = tuple(boxes[i])
            display_str = "{}: {}%".format(class_names[i].decode("ascii"),
                                           int(100 * scores[i]))
            color = colors[hash(class_names[i]) % len(colors)]
            image_pil = Image.fromarray(np.uint8(image)).convert("RGB")
            draw_bounding_box_on_image(
                image_pil,
                ymin,
                xmin,
                ymax,
                xmax,
                color,
                font,
                display_str_list=[display_str])
            np.copyto(image, np.array(image_pil))
    return image
    

    By Heiko Gorski, Source: https://commons.wikimedia.org/wiki/File:Naxos_Tavern

    image_url = "https://upload.wikimedia.org/wikipedia/commons/6/60/Naxos_Ta
    verna.jpg"
    downloaded_image_path = download_and_resize_image(image_url, 1280, 856, True)

    module_handle = "https://tfhub.dev/google/faster_rcnn/openimages_v4/incep
    tion_resnet_v2/1"

    detector = hub.load(module_handle).signatures['default']

    def load_img(path):
    img = tf.io.read_file(path)
    img = tf.image.decode_jpeg(img, channels=3)
    return img

    def run_detector(detector, path):
    img = load_img(path)

    converted_img = tf.image.convert_image_dtype(img,
                                                 tf.float32)[tf.newaxis, ...]
    start_time = time.time()
    result = detector(converted_img)
    end_time = time.time()
    
    result = {key: value.numpy() for key, value in result.items()}
    
    print("Found %d objects." % len(result["detection_scores"]))
    print("Inference time: ", end_time-start_time)
    
    image_with_boxes = draw_boxes(
        img.numpy(), result["detection_boxes"],
        result["detection_class_entities"], result["detection_scores"])
    
    display_image(image_with_boxes)
    

    run_detector(detector, downloaded_image_path)

  • Level 12

    @최해선
    alt text
    Jupyter notebook 통해서 실행을 하시면 결과 이미지를 바로 확인하실 수 있습니다

  • Level 3

    @Jose-goorm 그러면 이미지는 어떻게 확인할수있는 방법이 있습니까?

  • Level 12

    줄넘김은 아래와 같이 시도해보시기 바랍니다

    str1 = "abcd"\
        "efgh"
    
    str2 = ("가나다라"
            "마바사아"
           )
    
  • Level 12

    matplotlib 결과 이미지 표시는 현재 지원되지 않고 있습니다.
    Jupyter notebook 스택으로 컨테이너 생성하셔서 한번 시도해보시는 것도 추천 드립니다.

  • Level 10

    내용이 보기 힘든데 허브 에디터 문제일까요?ㅜ

  • Level 3

    추가적으로 줄넘김 \ 하는 저 방법이 맞는지 알려주시면 감사합니다

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