visualize.py

import os
import sys
import random
import itertools
import colorsys

import numpy as np
from skimage.measure import find_contours
import matplotlib.pyplot as plt
from matplotlib import patches, lines
from matplotlib.patches import Polygon
import IPython.display

def random_colors(N, bright=True):
    '''
    Generate random colors.
    To get visually distinct colors, generate them in HSV space then
    convert to RGB.
    '''
    brightness = 1.0 if bright else 0.7
    hsv = [(i / N, 1, brightness) for i in range(N)]
    colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv))
    random.shuffle(colors)
    return colors

def display_instances(image, boxes, class_ids, class_names,
                      scores=None, title="",
                      figsize=(16, 16), ax=None):
    '''
    boxes: [num_instance, (y1, x1, y2, x2, class_id)] in image coordinates.
    class_ids: [num_instances]
    class_names: list of class names of the dataset
    scores: (optional) confidence scores for each box
    figsize: (optional) the size of the image.
    '''
    # Number of instances
    N = boxes.shape[0]
    if not N:
        print("\n*** No instances to display *** \n")
    # else:
    #     assert boxes.shape[0] == masks.shape[-1] == class_ids.shape[0]

    if not ax:
        _, ax = plt.subplots(1, figsize=figsize)

    # Generate random colors
    colors = random_colors(N)

    # Show area outside image boundaries.
    height, width = image.shape[:2]
    ax.set_ylim(height + 10, -10)
    ax.set_xlim(-10, width + 10)
    ax.axis('off')
    ax.set_title(title)

    masked_image = image.astype(np.uint32).copy()
    for i in range(N):
        color = colors[i]

        # Bounding box
        if not np.any(boxes[i]):
            # Skip this instance. Has no bbox. Likely lost in image cropping.
            continue
        y1, x1, y2, x2 = boxes[i]
        y1, x1, y2, x2 = int(y1), int(x1), int(y2), int(x2)
        p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2,
                              alpha=0.7, linestyle="dashed",
                              edgecolor=color, facecolor='none')
        ax.add_patch(p)

        # Label
        class_id = class_ids[i]
        score = scores[i] if scores is not None else None
        label = class_names[class_id]
        x = random.randint(x1, (x1 + x2) // 2)
        caption = "{} {:.3f}".format(label, score) if score else label
        ax.text(x1, y1 + 8, caption,
                color='w', size=11, backgroundcolor="none")


    plt.imshow(image.astype(np.uint8))
    plt.show()
    
def draw_boxes(image, boxes=None, refined_boxes=None,
               captions=None, visibilities=None,
               title="", ax=None):
    '''Draw bounding boxes and segmentation masks with differnt
    customizations.
    boxes: [N, (y1, x1, y2, x2, class_id)] in image coordinates.
    refined_boxes: Like boxes, but draw with solid lines to show
        that they're the result of refining 'boxes'.
    captions: List of N titles to display on each box
    visibilities: (optional) List of values of 0, 1, or 2. Determine how
        prominant each bounding box should be.
    title: An optional title to show over the image
    ax: (optional) Matplotlib axis to draw on.
    '''
    # Number of boxes
    N = boxes.shape[0] if boxes is not None else refined_boxes.shape[0]

    # Matplotlib Axis
    if not ax:
        _, ax = plt.subplots(1, figsize=(16, 16))

    # Generate random colors
    colors = random_colors(N)

    # Show area outside image boundaries.
    margin = image.shape[0] // 10
    ax.set_ylim(image.shape[0] + margin, -margin)
    ax.set_xlim(-margin, image.shape[1] + margin)
    ax.axis('off')

    ax.set_title(title)

    for i in range(N):
        # Box visibility
        visibility = visibilities[i] if visibilities is not None else 1
        if visibility == 0:
            color = "gray"
            style = "dotted"
            alpha = 0.5
        elif visibility == 1:
            color = colors[i]
            style = "dotted"
            alpha = 1
        elif visibility == 2:
            color = colors[i]
            style = "solid"
            alpha = 1

        # Boxes
        if boxes is not None:
            if not np.any(boxes[i]):
                # Skip this instance. Has no bbox. Likely lost in cropping.
                continue
            y1, x1, y2, x2 = boxes[i]
            p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2,
                                  alpha=alpha, linestyle=style,
                                  edgecolor=color, facecolor='none')
            ax.add_patch(p)

        # Refined boxes
        if refined_boxes is not None and visibility > 0:
            ry1, rx1, ry2, rx2 = refined_boxes[i].astype(np.int32)
            p = patches.Rectangle((rx1, ry1), rx2 - rx1, ry2 - ry1, linewidth=2,
                                  edgecolor=color, facecolor='none')
            ax.add_patch(p)
            # Connect the top-left corners of the anchor and proposal
            if boxes is not None:
                ax.add_line(lines.Line2D([x1, rx1], [y1, ry1], color=color))

        # Captions
        if captions is not None:
            caption = captions[i]
            # If there are refined boxes, display captions on them
            if refined_boxes is not None:
                y1, x1, y2, x2 = ry1, rx1, ry2, rx2
            x = random.randint(x1, (x1 + x2) // 2)
            ax.text(x1, y1, caption, size=11, verticalalignment='top',
                    color='w', backgroundcolor="none",
                    bbox={'facecolor': color, 'alpha': 0.5,
                          'pad': 2, 'edgecolor': 'none'})

    ax.imshow(image.astype(np.uint8))