vision.py

def show_image_caption(image_path, description):
    import matplotlib.pyplot as plt
    from PIL import Image

    # Display the image
    fig = plt.figure(figsize=(8, 8))
    img = Image.open(image_path)
    caption_text = ''
    if (len(description.captions) == 0):
        caption_text = 'No caption detected'
    else:
        for caption in description.captions:
            caption_text = caption_text + " '{}'\n(Confidence: {:.2f}%)".format(caption.text, caption.confidence * 100)
    plt.title(caption_text)
    plt.axis('off')
    plt.imshow(img)

def show_image_analysis(image_path, analysis):
    import matplotlib.pyplot as plt
    from PIL import Image, ImageDraw
    import numpy as np

    # Display the image
    fig = plt.figure(figsize=(16, 8))
    a = fig.add_subplot(1,2,1)
    img = Image.open(image_path)
    
    # Get the caption
    caption_text = ''
    if (len(analysis.description.captions) == 0):
        caption_text = 'No caption detected'
    else:
        for caption in analysis.description.captions:
            caption_text = caption_text + " '{}'\n(Confidence: {:.2f}%)".format(caption.text, caption.confidence * 100)
    plt.title(caption_text)

    # Get objects
    if analysis.objects:
        # Draw a rectangle around each object
        for object in analysis.objects:
            r = object.rectangle
            bounding_box = ((r.x, r.y), (r.x + r.w, r.y + r.h))
            draw = ImageDraw.Draw(img)
            draw.rectangle(bounding_box, outline='magenta', width=5)
            plt.annotate(object.object_property,(r.x, r.y), backgroundcolor='magenta')

    # Get faces
    if analysis.faces:
        # Draw a rectangle around each face
        for face in analysis.faces:
            r = face.face_rectangle
            bounding_box = ((r.left, r.top), (r.left + r.width, r.top + r.height))
            draw = ImageDraw.Draw(img)
            draw.rectangle(bounding_box, outline='lightgreen', width=5)
            annotation = 'Person aged approxilately {}'.format(face.age)
            plt.annotate(annotation,(r.left, r.top), backgroundcolor='lightgreen')

    plt.axis('off')
    plt.imshow(img)

    # Add a second plot for addition details
    a = fig.add_subplot(1,2,2)

    # Get ratings
    ratings = 'Ratings:\n - Adult: {}\n - Racy: {}\n - Gore: {}'.format(analysis.adult.is_adult_content,
                                                                           analysis.adult.is_racy_content,
                                                                           analysis.adult.is_gory_content,)

    # Get tags
    tags = 'Tags:'
    for tag in analysis.tags:
        tags = tags + '\n - {}'.format(tag.name)

    # Print details

    details = '{}\n\n{}'.format(ratings, tags)
    a.text(0,0.4, details, fontsize=12)
    plt.axis('off')
    plt.show()