522 lines
20 KiB
Python
522 lines
20 KiB
Python
# Label_v6_OBB.py
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# ---------------------
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# Upgraded for YOLO-OBB (Oriented Bounding Boxes)
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# Features intuitive 3-step angled box drawing, dynamic view scaling,
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# interactive zooming, and multi-class tagging.
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import glob
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import os
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import random
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import cv2
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import numpy as np
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# --- CONFIGURATION ---
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OUTPUT_DIRECTORY = "dataset_v6_obb"
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FRAMES_TO_EXTRACT = 20 # Number of random anchor frames to find targets
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SCALE_FACTOR = 0.5 # Resize initial video to 1/2 size for easier viewing
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RANDOM_CROP_SIZE_RATIO = 0.5 # Random crop takes 50% width x 50% height of the frame
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# UI Display Constraints (Prevents tiny windows & makes small crops easy to see)
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MIN_WINDOW_WIDTH = 800
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MIN_WINDOW_HEIGHT = 600
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MAX_VIEW_SCALE = 10.0 # Maximum zoom multiplier for visual display
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HUD_HEIGHT = 40 # Height of the dedicated header bar above the image
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# Defined classification options (YOLO maps these to IDs: 0, 1, 2, 3...)
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CLASSIFICATION_OPTIONS = [
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"guardian",
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"interceptor",
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"sentinel",
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"rocket",
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"bomber",
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]
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# Distinct BGR color palette for each class
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CLASS_COLORS = [
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(255, 255, 0), # 0: Guardian (Cyan)
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(255, 0, 255), # 1: Interceptor (Magenta)
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(0, 255, 255), # 2: Sentinel (Yellow)
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(0, 0, 255), # 3: Rocket (Bright Red)
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(0, 255, 0), # 4: Bomber (Bright Green)
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(0, 165, 255), # 5: Orange
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(255, 0, 128), # 6: Purple
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]
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# ---------------------
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def get_obb_corners(p1, p2, p_mouse):
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"""Calculates the 4 corners of an oriented bounding box from a baseline and mouse position."""
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v = np.array(p2, dtype=float) - np.array(p1, dtype=float)
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length = np.linalg.norm(v)
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if length < 1e-5:
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return [p1, p1, p1, p1]
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u = v / length
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perp = np.array([-u[1], u[0]]) # Perpendicular unit vector
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v_mouse = np.array(p_mouse, dtype=float) - np.array(p1, dtype=float)
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d = np.dot(v_mouse, perp) # Signed distance from mouse to baseline
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c1 = np.array(p1, dtype=float)
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c2 = np.array(p2, dtype=float)
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c3 = c2 + d * perp
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c4 = c1 + d * perp
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return [
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tuple(np.round(c1).astype(int)),
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tuple(np.round(c2).astype(int)),
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tuple(np.round(c3).astype(int)),
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tuple(np.round(c4).astype(int))
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]
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def get_dataset_counts():
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"""Counts the number of existing OBB boxes by parsing YOLO text files."""
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counts = {option: 0 for option in CLASSIFICATION_OPTIONS}
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labels_dir = os.path.join(OUTPUT_DIRECTORY, "labels")
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if os.path.exists(labels_dir):
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for txt_file in glob.glob(os.path.join(labels_dir, "*.txt")):
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try:
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with open(txt_file, "r") as f:
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for line in f:
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parts = line.strip().split()
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# OBB format has 1 class_id + 8 coordinate values (9 total)
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if len(parts) >= 9:
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class_id = int(parts[0])
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if 0 <= class_id < len(CLASSIFICATION_OPTIONS):
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option = CLASSIFICATION_OPTIONS[class_id]
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counts[option] += 1
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except Exception:
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pass
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return counts
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def get_current_filename_base(param):
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"""Generates a unique filename base, appending crop coordinates if zoomed in."""
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video_base = os.path.splitext(os.path.basename(param["video_name"]))[0]
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base = f"{video_base}_frame_{param['frame_idx']}"
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if param["crop_box"] is not None:
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cx1, cy1, cx2, cy2 = param["crop_box"]
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base += f"_crop_{cx1}_{cy1}_{cx2}_{cy2}"
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return base
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def load_existing_annotations(param):
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"""Loads existing YOLO-OBB annotations (4 corner points) from disk."""
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filename_base = get_current_filename_base(param)
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label_path = os.path.join(param["labels_dir"], f"{filename_base}.txt")
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param["annotations"] = []
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if os.path.exists(label_path):
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img_h, img_w = param["frame"].shape[:2]
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try:
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with open(label_path, "r") as f:
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for line in f:
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parts = line.strip().split()
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if len(parts) >= 9:
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class_id = int(parts[0])
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pts = []
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for j in range(1, 9, 2):
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nx = float(parts[j])
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ny = float(parts[j+1])
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pts.append((int(nx * img_w), int(ny * img_h)))
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label = (
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CLASSIFICATION_OPTIONS[class_id]
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if 0 <= class_id < len(CLASSIFICATION_OPTIONS)
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else f"ID {class_id}"
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)
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param["annotations"].append((class_id, label, pts))
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except Exception as e:
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print(f" Could not load existing annotations: {e}")
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def apply_crop(param, crop_coords=None):
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"""Updates the working frame to either a cropped sub-region or the full screenshot."""
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if crop_coords is None:
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param["crop_box"] = None
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param["frame"] = param["full_frame"].copy()
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else:
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cx1, cy1, cx2, cy2 = crop_coords
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h, w = param["full_frame"].shape[:2]
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cx1, cx2 = max(0, min(cx1, w - 1)), max(0, min(cx2, w))
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cy1, cy2 = max(0, min(cy1, h - 1)), max(0, min(cy2, h))
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if (cx2 - cx1) < 15 or (cy2 - cy1) < 15:
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print(" Crop area too small! Aborting zoom.")
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return
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param["crop_box"] = (cx1, cy1, cx2, cy2)
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param["frame"] = param["full_frame"][cy1:cy2, cx1:cx2].copy()
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param["drawing_step"] = 0
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param["zooming"] = False
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load_existing_annotations(param)
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redraw_frame(param)
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def win_to_frame_coords(win_x, win_y, param):
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"""Converts UI window mouse coordinates back to native working frame coordinates."""
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adj_y = max(0, win_y - HUD_HEIGHT)
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scale = param.get("view_scale", 1.0)
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frame_x = int(win_x / scale)
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frame_y = int(adj_y / scale)
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h, w = param["frame"].shape[:2]
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frame_x = max(0, min(frame_x, w - 1))
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frame_y = max(0, min(frame_y, h - 1))
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return frame_x, frame_y
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def draw_hud(frame, param, view_scale):
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"""Draws an informative status banner in the dedicated top header area."""
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color = CLASS_COLORS[param["class_id"] % len(CLASS_COLORS)]
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zoom_str = "FULL" if param["crop_box"] is None else f"CROP ({view_scale:.1f}x VIEW)"
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step_msg = {
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0: "[Drag] Set Length | [SPACE] Class | [R] Rand Crop",
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1: "[Release] Lock Length Axis...",
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2: "[Move] Set Width -> [Click] Save OBB | [Right-Click] Cancel"
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}[param["drawing_step"]]
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label_str = f"[{zoom_str}] ACTIVE: [{param['class_id']}] {param['session_label'].upper()} | {step_msg}"
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cv2.rectangle(frame, (0, 0), (14, HUD_HEIGHT), color, -1)
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cv2.line(frame, (0, HUD_HEIGHT - 1), (frame.shape[1], HUD_HEIGHT - 1), (70, 70, 70), 1)
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cv2.putText(
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frame,
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label_str,
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(24, 25),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.45,
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(255, 255, 255),
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1,
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cv2.LINE_AA,
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)
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def redraw_frame(param, display_tags=True):
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"""Regenerates the display frame using dynamic view scaling and oriented polygon overlays."""
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h_frame, w_frame = param["frame"].shape[:2]
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scale_w = MIN_WINDOW_WIDTH / float(w_frame)
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scale_h = MIN_WINDOW_HEIGHT / float(h_frame)
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view_scale = max(1.0, min(scale_w, scale_h))
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view_scale = min(MAX_VIEW_SCALE, view_scale)
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param["view_scale"] = view_scale
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disp_w = int(w_frame * view_scale)
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disp_h = int(h_frame * view_scale)
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display_img = cv2.resize(param["frame"], (disp_w, disp_h), interpolation=cv2.INTER_LINEAR)
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fill_overlay = display_img.copy()
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border_overlay = display_img.copy()
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text_frame = display_img.copy()
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for ann in param["annotations"]:
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class_id, label, pts = ann
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color = CLASS_COLORS[class_id % len(CLASS_COLORS)]
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scaled_pts = np.array([[int(pt[0] * view_scale), int(pt[1] * view_scale)] for pt in pts], dtype=np.int32)
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scaled_pts = scaled_pts.reshape((-1, 1, 2))
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cv2.fillPoly(fill_overlay, [scaled_pts], color)
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cv2.polylines(border_overlay, [scaled_pts], True, color, 2)
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# Place text label near the first vertex
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dx1, dy1 = scaled_pts[0][0][0], scaled_pts[0][0][1]
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text_size, _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.45, 1)
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bg_width, bg_height = text_size[0] + 6, text_size[1] + 6
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cv2.rectangle(text_frame, (dx1, max(0, dy1 - bg_height)), (dx1 + bg_width, max(0, dy1)), color, -1)
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cv2.putText(text_frame, label, (dx1 + 3, max(12, dy1 - 4)), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 0), 1, cv2.LINE_AA)
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if display_tags:
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cv2.addWeighted(fill_overlay, 0.20, display_img, 0.80, 0, display_img)
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cv2.addWeighted(border_overlay, 0.70, display_img, 0.30, 0, display_img)
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cv2.addWeighted(text_frame, 0.30, display_img, 0.70, 0, display_img)
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final_display = cv2.copyMakeBorder(
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display_img, HUD_HEIGHT, 0, 0, 0, cv2.BORDER_CONSTANT, value=(30, 30, 30)
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)
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draw_hud(final_display, param, view_scale)
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param["display_frame"] = final_display
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cv2.imshow(param["window_name"], final_display)
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def save_annotations_to_file(param):
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"""Overwrites the YOLO-OBB text file with 8 corner coordinates and saves the image patch."""
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filename_base = get_current_filename_base(param)
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image_save_path = os.path.join(param["images_dir"], f"{filename_base}.jpg")
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label_save_path = os.path.join(param["labels_dir"], f"{filename_base}.txt")
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if len(param["annotations"]) == 0:
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if os.path.exists(label_save_path):
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os.remove(label_save_path)
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if os.path.exists(image_save_path):
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os.remove(image_save_path)
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print(f" Removed empty annotation files for {filename_base}")
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else:
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cv2.imwrite(image_save_path, param["frame"])
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img_h, img_w = param["frame"].shape[:2]
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with open(label_save_path, "w") as f:
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for ann in param["annotations"]:
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class_id, _, pts = ann
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norm_coords = []
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for pt in pts:
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norm_coords.append(f"{pt[0] / img_w:.6f}")
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norm_coords.append(f"{pt[1] / img_h:.6f}")
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f.write(f"{class_id} " + " ".join(norm_coords) + "\n")
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print(f" Updated OBB dataset for {filename_base} ({len(param['annotations'])} boxes)")
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def mouse_click_callback(event, x, y, flags, param):
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"""Handles 3-step OBB drawing, zooming, and undo actions."""
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display_frame = param["display_frame"]
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window_name = param["window_name"]
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# --- Right Click: Cancel active drawing OR Undo last box ---
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if event == cv2.EVENT_RBUTTONDOWN:
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if param["drawing_step"] > 0:
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param["drawing_step"] = 0
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print(" Cancelled active box drawing.")
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redraw_frame(param)
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elif param["annotations"]:
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removed = param["annotations"].pop()
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print(f" Undid last OBB ([{removed[0]}] {removed[1]})")
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save_annotations_to_file(param)
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redraw_frame(param)
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else:
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print(" No boxes left to undo on this frame!")
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return
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# --- Middle Click OR Shift + Left Click: Start Zoom/Crop Box ---
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is_shift_click = (event == cv2.EVENT_LBUTTONDOWN) and (flags & cv2.EVENT_FLAG_SHIFTKEY)
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if event == cv2.EVENT_MBUTTONDOWN or is_shift_click:
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param["zooming"] = True
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param["win_ix"], param["win_iy"] = x, y
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return
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# --- Standard Left Click Down ---
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if event == cv2.EVENT_LBUTTONDOWN and not param["zooming"]:
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if param["drawing_step"] == 0:
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# Step 1: Start baseline length axis
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param["drawing_step"] = 1
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param["p1_win"] = (x, y)
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redraw_frame(param)
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elif param["drawing_step"] == 2:
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# Step 3: Second click confirms width and locks OBB
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p1_f = win_to_frame_coords(*param["p1_win"], param)
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p2_f = win_to_frame_coords(*param["p2_win"], param)
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mouse_f = win_to_frame_coords(x, y, param)
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pts = get_obb_corners(p1_f, p2_f, mouse_f)
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param["annotations"].append((param["class_id"], param["session_label"], pts))
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param["drawing_step"] = 0
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save_annotations_to_file(param)
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redraw_frame(param)
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# --- Mouse Move: Live Preview ---
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elif event == cv2.EVENT_MOUSEMOVE:
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if param["zooming"]:
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temp = display_frame.copy()
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cv2.rectangle(temp, (param["win_ix"], param["win_iy"]), (x, y), (255, 255, 255), 2)
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cv2.imshow(window_name, temp)
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elif param["drawing_step"] == 1:
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# Preview length baseline
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temp = display_frame.copy()
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color = CLASS_COLORS[param["class_id"] % len(CLASS_COLORS)]
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cv2.line(temp, param["p1_win"], (x, y), color, 2)
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cv2.imshow(window_name, temp)
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elif param["drawing_step"] == 2:
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# Preview full oriented bounding box expanding to mouse position
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temp = display_frame.copy()
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color = CLASS_COLORS[param["class_id"] % len(CLASS_COLORS)]
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pts_win = get_obb_corners(param["p1_win"], param["p2_win"], (x, y))
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poly = np.array(pts_win, dtype=np.int32).reshape((-1, 1, 2))
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cv2.polylines(temp, [poly], True, color, 2)
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cv2.imshow(window_name, temp)
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# --- Left Click Release ---
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elif event == cv2.EVENT_LBUTTONUP:
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if param["zooming"]:
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param["zooming"] = False
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x1, y1 = win_to_frame_coords(param["win_ix"], param["win_iy"], param)
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x2, y2 = win_to_frame_coords(x, y, param)
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x1, x2 = min(x1, x2), max(x1, x2)
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y1, y2 = min(y1, y2), max(y1, y2)
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if (x2 - x1) >= 10 and (y2 - y1) >= 10:
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if param["crop_box"] is not None:
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off_x, off_y = param["crop_box"][:2]
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x1, x2 = x1 + off_x, x2 + off_x
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y1, y2 = y1 + off_y, y2 + off_y
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apply_crop(param, (x1, y1, x2, y2))
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else:
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cv2.imshow(window_name, display_frame)
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elif param["drawing_step"] == 1:
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# Step 2: Release locks baseline length, switches mouse to width mode
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if abs(x - param["p1_win"][0]) < 5 and abs(y - param["p1_win"][1]) < 5:
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# Ignore accidental micro-clicks
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param["drawing_step"] = 0
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redraw_frame(param)
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else:
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param["p2_win"] = (x, y)
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param["drawing_step"] = 2
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redraw_frame(param)
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def label_video_session():
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print("=========================================")
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print(" AI YOLO-OBB DATASET LABELER v6 ")
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print("=========================================\n")
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mp4_files = glob.glob("*.mp4")
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if not mp4_files:
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print("Error: No .mp4 files found in current directory.")
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return
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selected_video = random.choice(mp4_files)
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print(f"-> Selected Video File: '{selected_video}'")
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counts = get_dataset_counts()
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print("\n-----------------------------------------")
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print(" CURRENT OBB DATASET STATUS ")
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print("-----------------------------------------")
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for option, count in counts.items():
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print(f" • {option.capitalize():<12} : {count} OBBs logged")
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print("-----------------------------------------")
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session_class_id = 0
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session_label = CLASSIFICATION_OPTIONS[0]
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cap = cv2.VideoCapture(selected_video)
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if not cap.isOpened():
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print(f"Error: Could not open video file {selected_video}")
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return
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total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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num_frames = min(FRAMES_TO_EXTRACT, total_frames)
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frame_indices = sorted(random.sample(range(total_frames), num_frames))
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images_dir = os.path.join(OUTPUT_DIRECTORY, "images")
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labels_dir = os.path.join(OUTPUT_DIRECTORY, "labels")
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os.makedirs(images_dir, exist_ok=True)
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os.makedirs(labels_dir, exist_ok=True)
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print("\n" + "=" * 60)
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print(" HOW TO DRAW OBB BOXES")
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print("=" * 60)
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print("► 3-STEP ORIENTED BOX DRAWING:")
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print(" 1. [Left-Click & Drag] along the length (nose to tail of ship).")
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print(" 2. [Release Mouse] and move away to expand the box width.")
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print(" 3. [Left-Click Again] to lock and save the angled rectangle!")
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print("-" * 60)
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print("► GENERAL CONTROLS:")
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print(" [Right-Click] - Cancel active drawing OR Undo last box.")
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print(" [SPACEBAR] - SWITCH TARGET CLASS.")
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print(" [Shift + Drag] - Zoom into a custom cluster of ships.")
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print(" [R Key] - Jump to random 50% sub-crop.")
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print(" [X Key] - Reset zoom back to full screenshot.")
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print(" [ENTER Key] - JUMP to NEXT frame / Save background.")
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print(" [Right / Left Arrow] - Step FORWARD/BACKWARD 10 frames.")
|
|
print(" [Q Key] - Quit and save all progress.")
|
|
print("=" * 60)
|
|
input("\nPress ENTER when you are ready to begin...")
|
|
|
|
LEFT_KEYS = [81, 2, 2424832, 65361, 63234]
|
|
RIGHT_KEYS = [83, 3, 2490368, 65363, 63235]
|
|
|
|
i = 0
|
|
current_frame = frame_indices[i]
|
|
window_name = "YOLO-OBB Labeler v6"
|
|
cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)
|
|
cv2.moveWindow(window_name, 20, 20)
|
|
|
|
while i < len(frame_indices):
|
|
cap.set(cv2.CAP_PROP_POS_FRAMES, current_frame)
|
|
ret, frame = cap.read()
|
|
if not ret:
|
|
i += 1
|
|
if i < len(frame_indices): current_frame = frame_indices[i]
|
|
continue
|
|
|
|
frame_resized = cv2.resize(frame, (0, 0), fx=SCALE_FACTOR, fy=SCALE_FACTOR)
|
|
cv2.setWindowTitle(window_name, f"YOLO-OBB Labeler v6 | Spot {i+1}/{num_frames} (Frame {current_frame})")
|
|
|
|
session_state = {
|
|
"full_frame": frame_resized,
|
|
"frame": frame_resized.copy(),
|
|
"display_frame": frame_resized.copy(),
|
|
"crop_box": None,
|
|
"view_scale": 1.0,
|
|
"images_dir": images_dir,
|
|
"labels_dir": labels_dir,
|
|
"frame_idx": current_frame,
|
|
"window_name": window_name,
|
|
"video_name": selected_video,
|
|
"class_id": session_class_id,
|
|
"session_label": session_label,
|
|
"drawing_step": 0, # 0: Idle, 1: Dragging baseline, 2: Setting width
|
|
"zooming": False,
|
|
"win_ix": -1,
|
|
"win_iy": -1,
|
|
"p1_win": (0, 0),
|
|
"p2_win": (0, 0),
|
|
"annotations": [],
|
|
}
|
|
|
|
load_existing_annotations(session_state)
|
|
redraw_frame(session_state)
|
|
cv2.setMouseCallback(window_name, mouse_click_callback, session_state)
|
|
|
|
while True:
|
|
key = cv2.waitKeyEx(1)
|
|
|
|
if key == 32 or key == ord(" "):
|
|
session_state["class_id"] = (session_state["class_id"] + 1) % len(CLASSIFICATION_OPTIONS)
|
|
session_state["session_label"] = CLASSIFICATION_OPTIONS[session_state["class_id"]]
|
|
redraw_frame(session_state)
|
|
elif key == ord("r") or key == ord("R"):
|
|
h, w = session_state["full_frame"].shape[:2]
|
|
crop_w, crop_h = int(w * RANDOM_CROP_SIZE_RATIO), int(h * RANDOM_CROP_SIZE_RATIO)
|
|
rx1, ry1 = random.randint(0, w - crop_w), random.randint(0, h - crop_h)
|
|
apply_crop(session_state, (rx1, ry1, rx1 + crop_w, ry1 + crop_h))
|
|
elif key == ord("x") or key == ord("X"):
|
|
if session_state["crop_box"] is not None:
|
|
apply_crop(session_state, None)
|
|
elif key == ord("\t"):
|
|
redraw_frame(session_state, display_tags=False)
|
|
elif key in [13, 10]:
|
|
i += 1
|
|
if i < len(frame_indices): current_frame = frame_indices[i]
|
|
break
|
|
elif key in RIGHT_KEYS:
|
|
if current_frame < total_frames - 10: current_frame += 10
|
|
break
|
|
elif key in LEFT_KEYS:
|
|
if current_frame > 0: current_frame -= 10
|
|
break
|
|
elif key == ord("q") or key == ord("Q") or (key & 0xFF) in [ord("q"), ord("Q")]:
|
|
cap.release()
|
|
cv2.destroyAllWindows()
|
|
return
|
|
|
|
cap.release()
|
|
cv2.destroyAllWindows()
|
|
print(f"\nSession finished! OBB Dataset saved to '{OUTPUT_DIRECTORY}'.")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
label_video_session()
|