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import os
import yaml
import numpy as np
# Configuration
DATASET_BASE_DIR = "dataset"
DATA_YAML_PATH = os.path.join(DATASET_BASE_DIR, "data.yaml")
SPLIT_TO_VIEW = "train"
IMAGE_DIR = os.path.join(DATASET_BASE_DIR, SPLIT_TO_VIEW, "images")
LABEL_DIR = os.path.join(DATASET_BASE_DIR, SPLIT_TO_VIEW, "labels")
# Default window size and scale factor
DEFAULT_MAX_WIDTH = 1280
DEFAULT_MAX_HEIGHT = 720
DEFAULT_SCALE_FACTOR = 1.0
# Load Class Names
try:
with open(DATA_YAML_PATH, "r") as f:
data_yaml = yaml.safe_load(f)
CLASS_NAMES = data_yaml["names"]
print(f"Found these classes: {CLASS_NAMES}")
except Exception as e:
print(f"Couldn't read the class names from {DATA_YAML_PATH}: {e}")
CLASS_NAMES = None
# Visualization Function
def visualize_yolo_annotations(image_dir, label_dir, class_names):
image_files = sorted(
[
f
for f in os.listdir(image_dir)
if f.lower().endswith((".png", ".jpg", ".jpeg"))
]
)
num_images = len(image_files)
current_index = 0
scale_factor = DEFAULT_SCALE_FACTOR
# Window name
window_name = "YOLO Annotations - n:next p:prev q:quit +/-:zoom r:reset"
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
while True:
if current_index < 0:
current_index = 0
if current_index >= num_images:
current_index = num_images - 1
img_filename = image_files[current_index]
img_path = os.path.join(image_dir, img_filename)
label_filename = os.path.splitext(img_filename)[0] + ".txt"
label_path = os.path.join(label_dir, label_filename)
# Load Image
image = cv2.imread(img_path)
if image is None:
print(f"Can't load this image: {img_path}")
key = cv2.waitKey(0)
if key == ord("q"):
break
elif key == ord("n"):
current_index += 1
continue
elif key == ord("p"):
current_index -= 1
continue
else:
continue
orig_h, orig_w, _ = image.shape
vis_image = image.copy()
# Load and Draw Annotations
if os.path.exists(label_path):
try:
with open(label_path, "r") as f:
for line in f:
parts = line.strip().split()
if len(parts) >= 5:
(
class_id,
x_center_norm,
y_center_norm,
width_norm,
height_norm,
) = map(float, parts[:5])
class_id = int(class_id)
# Denormalize coordinates
box_w = width_norm * orig_w
box_h = height_norm * orig_h
center_x = x_center_norm * orig_w
center_y = y_center_norm * orig_h
x_min = int(center_x - (box_w / 2))
y_min = int(center_y - (box_h / 2))
x_max = int(center_x + (box_w / 2))
y_max = int(center_y + (box_h / 2))
# Draw bounding box (Green color)
cv2.rectangle(
vis_image,
(x_min, y_min),
(x_max, y_max),
(0, 255, 0),
2,
)
# Draw label
if class_names and 0 <= class_id < len(class_names):
label = class_names[class_id]
else:
label = f"Class_{class_id}"
# Put label text above the box
(text_width, text_height), baseline = cv2.getTextSize(
label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1
)
cv2.rectangle(
vis_image,
(x_min, y_min - text_height - baseline),
(x_min + text_width, y_min),
(0, 255, 0),
-1,
) # Filled background
cv2.putText(
vis_image,
label,
(x_min, y_min - baseline),
cv2.FONT_HERSHEY_SIMPLEX,
0.5,
(0, 0, 0),
1,
) # Black text
except Exception as e:
print(f"Problem reading label file {label_path}: {e}")
else:
print(f"No label file for this image: {label_path}")
# Add display information
display_text = f"{SPLIT_TO_VIEW}: {img_filename} ({current_index + 1}/{num_images}) - Scale: {scale_factor:.2f}x"
cv2.putText(
vis_image,
display_text,
(10, 25),
cv2.FONT_HERSHEY_SIMPLEX,
0.7,
(0, 0, 255),
2,
)
# Resize image to fit window while maintaining aspect ratio
display_h, display_w = int(orig_h * scale_factor), int(orig_w * scale_factor)
# Resize if the image is too large or too small (based on scale_factor)
if display_w != orig_w or display_h != orig_h:
vis_image = cv2.resize(
vis_image,
(display_w, display_h),
interpolation=cv2.INTER_AREA if scale_factor < 1 else cv2.INTER_LINEAR,
)
# Resize window to fit the content (with limits)
window_w = min(display_w, DEFAULT_MAX_WIDTH)
window_h = min(display_h, DEFAULT_MAX_HEIGHT)
cv2.resizeWindow(window_name, window_w, window_h)
# Display Image
cv2.imshow(window_name, vis_image)
# Key Handling
key = cv2.waitKey(0)
if key == ord("q"):
break
elif key == ord("n"):
current_index += 1
elif key == ord("p"):
current_index -= 1
elif key == ord("+") or key == ord("="):
scale_factor *= 1.2
elif key == ord("-") or key == ord("_"):
scale_factor /= 1.2
elif key == ord("r"):
scale_factor = DEFAULT_SCALE_FACTOR
elif key == 32:
if (
cv2.getWindowProperty(window_name, cv2.WND_PROP_FULLSCREEN)
== cv2.WINDOW_FULLSCREEN
):
cv2.setWindowProperty(
window_name, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_NORMAL
)
else:
cv2.setWindowProperty(
window_name, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN
)
cv2.destroyAllWindows()
print("All done viewing annotations!")
# Run Visualization
if __name__ == "__main__":
if not os.path.exists(IMAGE_DIR) or not os.path.exists(LABEL_DIR):
print(
f"Can't find images or labels. Check these folders: {IMAGE_DIR} and {LABEL_DIR}"
)
elif CLASS_NAMES is None:
print("No class names found. Make sure data.yaml exists and is formatted correctly.")
else:
visualize_yolo_annotations(IMAGE_DIR, LABEL_DIR, CLASS_NAMES)
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