refactor: single predict.py entrypoint (production + CLI), archive experiments
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import cv2
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import os
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import json
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import numpy as np
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# State constants
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STATE_TRUCK = 0
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STATE_DETECTION = 1
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STATE_LINE = 2
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STATE_DONE = 3
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state = STATE_TRUCK
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points_truck = []
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points_detection = []
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points_line = []
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def click_event(event, x, y, flags, params):
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global state
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if event == cv2.EVENT_LBUTTONDOWN:
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if state == STATE_TRUCK:
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points_truck.append([x, y])
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print(f"Truck Area - Point {len(points_truck)}: [{x}, {y}]")
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if len(points_truck) == 4:
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state = STATE_DETECTION
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print("\n-> Area Truk Berhasil Dipilih (4 titik).")
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print("-> SILAHKAN PILIH AREA DETEKSI (Klik Kiri 4 Titik secara berurutan: Top-Left, Top-Right, Bottom-Right, Bottom-Left).")
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elif state == STATE_DETECTION:
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points_detection.append([x, y])
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print(f"Detection Area - Point {len(points_detection)}: [{x}, {y}]")
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if len(points_detection) == 4:
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state = STATE_LINE
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print("\n-> Area Deteksi Berhasil Dipilih (4 titik).")
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print("-> SILAHKAN PILIH COUNT LINE (Klik Kiri Titik Mulai dan Titik Selesai).")
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elif state == STATE_LINE:
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points_line.append([x, y])
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print(f"Count Line - Point {len(points_line)}: [{x}, {y}]")
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if len(points_line) == 2:
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state = STATE_DONE
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print("\n-> Count Line Berhasil Dipilih.")
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print("-> Semua koordinat telah lengkap! Tekan 's' untuk mencetak & menyimpan koordinat.")
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draw_frame()
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def draw_frame():
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img_copy = img.copy()
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h, w, _ = img_copy.shape
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# 1. Draw Area Truk (Orange Polygon)
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for pt in points_truck:
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cv2.circle(img_copy, tuple(pt), 5, (0, 165, 255), -1)
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if len(points_truck) == 4:
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pts = np.array(points_truck, np.int32)
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cv2.polylines(img_copy, [pts], True, (0, 165, 255), 2)
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cv2.putText(img_copy, "TRUCK AREA", tuple(points_truck[0]),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 165, 255), 1)
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# 2. Draw Area Deteksi (Cyan Polygon)
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for pt in points_detection:
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cv2.circle(img_copy, tuple(pt), 5, (255, 255, 0), -1)
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if len(points_detection) == 4:
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pts = np.array(points_detection, np.int32)
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cv2.polylines(img_copy, [pts], True, (255, 255, 0), 2)
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cv2.putText(img_copy, "DETECTION AREA", tuple(points_detection[0]),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 0), 1)
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# 3. Draw Count Line (Magenta Line)
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if len(points_line) > 0:
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cv2.circle(img_copy, tuple(points_line[0]), 5, (255, 0, 255), -1)
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if len(points_line) == 2:
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cv2.line(img_copy, tuple(points_line[0]), tuple(points_line[1]), (255, 0, 255), 3)
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# Draw midpoint circle
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mid_x = int((points_line[0][0] + points_line[1][0]) / 2)
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mid_y = int((points_line[0][1] + points_line[1][1]) / 2)
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cv2.circle(img_copy, (mid_x, mid_y), 6, (0, 255, 0), -1)
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cv2.putText(img_copy, f"LINE (y={mid_y})", (mid_x + 10, mid_y - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 255), 1)
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# Draw Instruction Overlay on Top
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overlay_y = 35
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if state == STATE_TRUCK:
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txt = f"1. PILIH AREA TRUK (Klik Kiri 4 Titik, saat ini: {len(points_truck)}/4)"
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color = (0, 165, 255)
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elif state == STATE_DETECTION:
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txt = f"2. PILIH AREA DETEKSI (Klik Kiri 4 Titik, saat ini: {len(points_detection)}/4)"
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color = (255, 255, 0)
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elif state == STATE_LINE:
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txt = f"3. PILIH COUNT LINE (Klik Kiri Titik Awal lalu Titik Akhir, saat ini: {len(points_line)}/2)"
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color = (255, 0, 255)
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else:
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txt = "SELESAI! Tekan 's' untuk simpan atau 'c' untuk ulang."
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color = (0, 255, 0)
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# Draw background panel for text
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cv2.rectangle(img_copy, (10, 10), (w - 10, 50), (0, 0, 0), -1)
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cv2.putText(img_copy, txt, (20, overlay_y), cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
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cv2.imshow('Interactive 4-Point Zone Selector', img_copy)
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if __name__ == "__main__":
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source_img = "gambar_terbaru.jpg" if os.path.exists("gambar_terbaru.jpg") else "calib_frame.jpg"
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video_source = "0727.mp4"
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if os.path.exists(source_img):
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img = cv2.imread(source_img)
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print(f"Loaded image: {source_img}")
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elif os.path.exists(video_source):
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print(f"Grabbing frame from video: {video_source}")
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cap = cv2.VideoCapture(video_source)
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for _ in range(10):
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ret, img = cap.read()
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cap.release()
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if not ret:
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print("Error: Could not grab frame from video.")
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exit(1)
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else:
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print("Error: Neither calib_frame.jpg nor the video file exists.")
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exit(1)
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cv2.namedWindow('Interactive 4-Point Zone Selector')
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cv2.setMouseCallback('Interactive 4-Point Zone Selector', click_event)
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print("\n=== OpenCV 4-Point Zone Coordinate Selector ===")
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print("Instructions:")
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print("1. Left-click to select coordinates for each step.")
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print("2. Press 'c' at any time to clear selection and restart.")
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print("3. Press 's' when done to print python snippets and save to zones_output.json.")
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print("4. Press 'q' or 'ESC' to quit.")
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print("========================================\n")
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print("-> SILAHKAN PILIH AREA TRUK (Klik Kiri 4 Titik secara berurutan: Top-Left, Top-Right, Bottom-Right, Bottom-Left).")
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draw_frame()
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while True:
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key = cv2.waitKey(1) & 0xFF
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if key == ord('c') or key == ord('C'):
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state = STATE_TRUCK
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points_truck = []
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points_detection = []
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points_line = []
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print("\nCleared selection. Restarting from Step 1 (Area Truk)...")
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draw_frame()
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elif key == ord('s') or key == ord('S'):
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if state != STATE_DONE:
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print(f"Warning: Harap selesaikan semua langkah terlebih dahulu. State saat ini: {state}")
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continue
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lx1, ly1 = points_line[0]
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lx2, ly2 = points_line[1]
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line_y_avg = int((ly1 + ly2) / 2)
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output_data = {
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"truck_poly": points_truck,
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"detection_poly": points_detection,
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"count_line": {
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"x_start": lx1, "x_end": lx2, "y": line_y_avg
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}
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}
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# Print configuration code snippets
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print("\n" + "="*50)
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print("KOORDINAT BERHASIL DI-GENERATE!")
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print("="*50)
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print("\n--- SALIN KODE DI BAWAH INI KE predict.py ---\n")
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print(f" # 1. Detection Area (4-point Polygon)")
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print(f" detection_poly_pts = [")
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for pt in points_detection:
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print(f" [int({pt[0]} * scale_x), int({pt[1]} * scale_y)],")
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print(f" ]")
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print(f" detection_polygon = Polygon(detection_poly_pts)")
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print()
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print(f" # 2. Count Line coordinates")
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print(f" static_line_y = int({line_y_avg} * scale_y)")
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print(f" static_line_x_start = int({lx1} * scale_x)")
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print(f" static_line_x_end = int({lx2} * scale_x)")
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print()
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print(f" # 3. Truck Area (4-point Polygon for presence check)")
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print(f" truck_poly_pts = [")
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for pt in points_truck:
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print(f" [int({pt[0]} * scale_x), int({pt[1]} * scale_y)],")
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print(f" ]")
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print(f" truck_polygon = Polygon(truck_poly_pts)")
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print()
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# Calculate bounding box of truck_polygon to maintain backward compatibility with static_roi
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tx_coords = [p[0] for p in points_truck]
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ty_coords = [p[1] for p in points_truck]
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min_tx, max_tx = min(tx_coords), max(tx_coords)
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min_ty, max_ty = min(ty_coords), max(ty_coords)
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print(f" static_roi = TruckROI(")
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print(f" x1=int({min_tx} * scale_x),")
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print(f" y1=int({min_ty} * scale_y),")
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print(f" x2=int({max_tx} * scale_x),")
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print(f" y2=int({max_ty} * scale_y),")
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print(f" line_y=static_line_y,")
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print(f" confidence=1.0")
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print(f" )")
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print("\n" + "="*50)
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# Save to json file
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with open("zones_output.json", "w") as f:
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json.dump(output_data, f, indent=4)
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print("Koordinat juga telah disimpan ke 'zones_output.json'\n")
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elif key == ord('q') or key == 27:
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break
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cv2.destroyAllWindows()
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