visualize_bboxes_on_image

utils/remove_duplicates.py

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+def remove_duplicates(items: list, key=lambda x: x, show_process=False):
+    '''
+    Remove duplicates from a list of items
+    Args:
+      items: List of items
+      key: Function to get the key of the item
+      show_process: Whether to show the process or not
+    Returns:
+      List: List of items without duplicates
+    '''
+    progress = lambda x, *, desc: x
+    if show_process:
+        import tqdm
+        progress = tqdm.tqdm
+    return list({key(item): item for item in progress(items, desc='Deduping...')}.values())

utils/show_tile_images.py

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+from utils.fig2img import fig2img
+import matplotlib.pyplot as plt
+import numpy as np
+from PIL import Image
+from typing import List
+
+def show_tile_images(
+    images: List[np.ndarray | Image.Image],
+    width_parts: int,
+    figsize = None,
+    space = 0.0,
+    pad = False,
+    figcolor = 'white',
+    titles: List[str] = None,
+    title_color: str = None,
+    title_background_color: str = None,
+    title_font_size: int = None):
+  '''
+  Show images in a tile format
+  Args:
+    images: List of images to show
+    width_parts: Number of images to show in a row
+    figsize: Size of the figure
+    space: Space between images
+    pad: Whether to pad the images or not
+    figcolor: Background color of the figure
+    titles: Titles of the images
+    title_color: Color of the title
+    title_background_color: Background color of the title
+    title_font_size: Font size of the title
+  Returns:
+    Image: Image of the figure
+  '''
+  height = int(np.ceil(len(images) / width_parts))
+  fig, axs = plt.subplots(height, width_parts, figsize=figsize if figsize != None else (8 * 2, 12 * height))
+  fig.patch.set_facecolor(figcolor)
+  axes = axs.flatten() if isinstance(axs, np.ndarray) else [axs]
+  titles = (titles or []) + np.full(len(images) - len(titles or []), None).tolist()
+  for img, ax, title in zip(images, axes, titles):
+    if title:
+      params = {k: v for k, v in { 'color': title_color, 'backgroundcolor': title_background_color, 'fontsize': title_font_size }.items() if v is not None}
+      ax.set_title(title, **params)
+    ax.imshow(img.convert("RGB") if not isinstance(img, np.ndarray) else img)
+    ax.axis('off')
+  if pad:
+    fig.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=space, hspace=space)
+    fig.tight_layout(h_pad=space, w_pad = space, pad = space)
+  else:
+    fig.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=space, hspace=space)
+    fig.tight_layout(h_pad=space, w_pad = space, pad = 0)
+  plt.margins()
+  plt.close()
+  return fig2img(fig)

utils/visualize_bboxes_on_image.py

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+# This file is used to visualize bounding boxes on an image
+from urllib.parse import urlparse
+from PIL import Image, ImageDraw, ImageFont
+import numpy as np
+import requests
+from typing import List
+from functools import cache
+
+@cache
+def get_font(path_or_url: str = 'https://github.com/googlefonts/roboto/raw/main/src/hinted/Roboto-Regular.ttf', size: int = 10):
+  if urlparse(path_or_url).scheme in ["http", "https"]: # Online
+      return ImageFont.truetype(requests.get(path_or_url, stream=True).raw, size=size)
+  else: # Local
+    return ImageFont.truetype(path_or_url, size=size)
+
+def visualize_bboxes_on_image(
+    image: Image.Image,
+    bboxes: List[List[int]],
+    titles: List[str] = None,
+    width = 2,
+    bbox_color="red",
+    label_text_color="black",
+    label_rectangle_color="red",
+    convert_to_x0y0x1y1 = None,
+    label_text_padding = 2,
+    label_rectangle_left_padding=10,
+    label_rectangle_top_padding=10,
+    label_text_size = 10) -> Image.Image:
+  '''
+  Visualize bounding boxes on an image
+  Args:
+    image: Image to visualize
+    bboxes: List of bounding boxes
+    titles: Titles of the bounding boxes
+    width: Width of the bounding box
+    bbox_color: Color of the bounding box
+    label_text_color: Color of the label text
+    label_rectangle_color: Color of the label rectangle
+    convert_to_x0y0x1y1: Function to convert bounding box to x0y0x1y1 format
+    label_text_padding: Padding of the label text
+    label_rectangle_left_padding: Left padding of the label rectangle
+    label_rectangle_top_padding: Top padding of the label rectangle
+    label_text_size: Font size of the label text
+  Returns:
+    Image: Image with bounding boxes'''
+  image = image.copy().convert("RGB")
+  draw = ImageDraw.Draw(image)
+  font = get_font(size = label_text_size)
+  titles = (titles or []) + np.full(len(bboxes) - len(titles or []), None).tolist()
+  for bbox, title in zip(bboxes, titles):
+    x0, y0, x1, y1 = convert_to_x0y0x1y1(bbox) if convert_to_x0y0x1y1 is not None else bbox
+    draw.rectangle([x0, y0, x1, y1], outline=bbox_color, width=width)
+    if title is not None:
+      title = title + " " + str(bbox)
+      text_position = (x0 + label_rectangle_left_padding, y0 - label_rectangle_top_padding)
+      text_bbox_left, text_bbox_top, text_bbox_right, text_bbox_bottom = draw.textbbox(text_position, title, font=font)
+      draw.rectangle(
+        (
+          text_bbox_left - label_text_padding, 
+          text_bbox_top - label_text_padding, 
+          text_bbox_right + label_text_padding, 
+          text_bbox_bottom + label_text_padding
+        ), 
+        fill=label_rectangle_color)
+      draw.text(text_position, title, font=font, fill=label_text_color)
+  return image