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threading.Thread< /code>):
threading.Thread(target=video_capture_thread, daemon=True).start()

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ret, frame = cap.read()

frame = cv2.resize(frame, target_resolution)
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

if detection_active:
process_frame = frame_gray
detection_time = time.time()
detection_result = check_detection_region(process_frame, current_detection_region,
last_process_time, last_check_time)
# print("*"*10, f"Detection Used Time: {time.time()- detection_time}", "*"*10, "\n")
if detection_result:
process_result(detection_result)
for i, region in enumerate(current_detection_region):
cv2.rectangle(frame_rgb,
(region[0], region[1]),
(region[2], region[3]),
(0, 255, 0), 5)
cv2.putText(frame_rgb,
text=f"Region-{i}",
org=(int(region[0]), int(region[1] - 10)),
fontFace= cv2.FONT_HERSHEY_SIMPLEX,
fontScale=1.2,
color=(0, 255, 0),
thickness=4)
frame_buffer.append(frame_rgb)
frame_ready.set()
time.sleep(0.01)
< /code>
2 、 Auswahl der interaktiven Region durch Canvas-Zeichnung
3 、 Asynchronous OCR-Verarbeitung in ausgewählten Regionen < /p>
ocr = PaddleOCR(
det_model_dir="./ch_PP-OCRv4_det_infer",
rec_model_dir="./ch_PP-OCRv4_rec_infer",
use_angle_cls=True,
lang="en",
log_level='ERROR'
)

def preprocess_bbox(region, frame):
x1, y1, x2, y2 = region
x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
if x1 > x2:
x1, x2 = x2, x1
if y1 > y2:
y1, y2 = y2, y1

height, width = frame.shape[:2]
x1 = max(0, min(x1, width - 1))   # 防止 x1 >= width
x2 = max(0, min(x2, width - 1))
y1 = max(0, min(y1, height - 1))
y2 = max(0, min(y2, height - 1))
return x1, y1, x2, y2

def change_num(region, text):
if region in [2, 3]:
if float(text)> 999:
return float(text)/100
elif region in [1, 4, 5, 6, 7, 8, 9]:
if float(text)> 100:
return float(text)/10
elif region in [0, 10, 11]:
if float(text)>  10:
return float(text)/100
return text

def check_detection_region(frame, detection_region, last_process_time, last_check_time):
region_data = {}
process_time_lock = threading.Lock()

for region_idx in range(len(detection_region)):
region_key = region_idx
rd = {
'detection_cache': [],
'last_cache_clear': time.time(),
'datetime_info': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
'last_process_time': 0.0
}
region_data[region_key] = rd

# max_workers = min(len(detection_region), os.cpu_count())
max_workers = 2
alarm_result = []
with ThreadPoolExecutor(max_workers= max_workers) as executor:
futures = []
futures = {executor.submit(process_region, region_idx, region,
frame, region_data,
last_process_time, last_check_time,
process_time_lock, ocr)
for region_idx, region in enumerate(detection_region)}
future_process_time = time.time()
for future in as_completed(futures):
try:
result = future.result()
if result:
alarm_result.append(result)
except Exception as e:
continue
print("*"*10, f"Process Time:{time.time()- future_process_time} Rgions: {len(detection_region)}-{len(list(set(detection_region)))}", "*"*10)
if alarm_result:
return alarm_result
else:
return None

def process_region(region_idx, region, frame, region_data, last_process_time,
last_check_time, process_time_lock, ocr= None
):
current_time = time.time()
# with process_time_lock:
# last_proc = last_process_time.get(region_idx, 0.0)
# last_check = last_check_time.get(region_idx, 0.0)
# if (current_time - last_proc < PROCESS_INTERVAL or
#     current_time - last_check < CHECK_INTERVAL):
#     return None
last_proc = last_process_time.get(region_idx, 0.0)
last_check_time[region_idx] = current_time
last_process_time[region_idx] = abs(current_time- last_proc)

region_key = region_idx
rd = region_data.get(region_key, None)
rd['last_process_time'] = current_time

x1, y1, x2, y2 = preprocess_bbox(region, frame)
roi = frame[y1:y2, x1:x2]
if roi.size == 0:
print(f"{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
return None

ocr_time = time.time()
ocr_result = ocr.ocr(roi, cls=True)
if not ocr_result:
print(f"ERROR: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
return None

# 处理识别结果
current_time = time.time()
date_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
for line in ocr_result:
for detection in line:
text, conf = detection[1]
print(f"{date_time}-{time.time()- ocr_time}-Region（{region}）：{region_idx} Text: {text}, Conf: {conf}")
if conf >  0.7 and re.match(r"(\d+(\.\d+)?)", text):
match = re.match(r"(\d+(\.\d+)?)", text)
current_value = float(change_num(region= region_idx, text= match.group(1)))
rd['detection_cache'].append({
'match_text': current_value,
'conf': conf,
'time': current_time,
'ocr_text': text
})

# if (current_time - rd['last_cache_clear'] >= 1) and rd['detection_cache']:
best = max(rd['detection_cache'], key=lambda x: x['conf'])
rd['detection_cache'][:] = []
rd['last_cache_clear'] = current_time

return {
'time': current_time,
'region_id': region_key,
'date_time': date_time,
'value': {
'num': best['match_text'],
'conf': round(best['conf'], 4),
'raw_text': best['ocr_text']
}
}
< /code>
Es gibt einige Ergebnisse: < /p>
2025-03-31 17:15:22-0.3458406925201416-Region（(748, 1100, 851, 1177)）：0 Text: 31, Conf: 0.9988272190093994
2025-03-31 17:15:22-0.3458406925201416-Region（(1014, 1158, 1100, 1238)）：1 Text: 31, Conf: 0.9988272190093994
2025-03-31 17:15:22-0.3442258834838867-Region（(1958, 1897, 2025, 1977)）：2 Text: 06, Conf: 0.9809097051620483
2025-03-31 17:15:23-0.22141623497009277-Region（(2332, 1916, 2416, 1987)）：5 Text: 82, Conf: 0.9945308566093445
2025-03-31 17:15:23-0.30546092987060547-Region（(886, 1555, 972, 1625)）：7 Text: 195, Conf: 0.9964171051979065
2025-03-31 17:15:23-0.1500873565673828-Region（(598, 1552, 665, 1612)）：9 Text: 130, Conf: 0.9943342804908752
********** Process Time:1.477724552154541 Rgions: 10-10 **********
2025-03-31 17:15:24-0.38674497604370117-Region（(1014, 1158, 1100, 1238)）：1 Text: 31, Conf: 0.9986810088157654
2025-03-31 17:15:24-0.3962728977203369-Region（(748, 1100, 851, 1177)）：0 Text: 2025, Conf: 0.9948824644088745
2025-03-31 17:15:24-0.3871188163757324-Region（(1958, 1897, 2025, 1977)）：2 Text: 36, Conf: 0.9956271648406982
2025-03-31 17:15:24-0.3814249038696289-Region（(2092, 1916, 2163, 1993)）：3 Text: 36, Conf: 0.9956271648406982
2025-03-31 17:15:24-0.4036712646484375-Region（(2332, 1916, 2416, 1987)）：5 Text: 82, Conf: 0.995288610458374
2025-03-31 17:15:25-0.3978700637817383-Region（(886, 1555, 972, 1625)）：7 Text: 195, Conf: 0.9958855509757996
2025-03-31 17:15:25-0.7991609573364258-Region（(739, 1529, 812, 1596)）：6 Text: 133, Conf: 0.9976328015327454
2025-03-31 17:15:25-0.2980964183807373-Region（(598, 1552, 665, 1612)）：9 Text: 130, Conf: 0.9968142509460449
********** Process Time:2.189676523208618 Rgions: 10-10 **********
2025-03-31 17:15:26-0.4011368751525879-Region（(748, 1100, 851, 1177)）：0 Text: 2025, Conf: 0.9921661615371704
2025-03-31 17:15:26-0.43567562103271484-Region（(1014, 1158, 1100, 1238)）：1 Text: 31, Conf: 0.9990317821502686
2025-03-31 17:15:26-0.22664427757263184-Region（(2092, 1916, 2163, 1993)）：3 Text: 36, Conf: 0.9965022802352905
2025-03-31 17:15:26-0.40086793899536133-Region（(1958, 1897, 2025, 1977)）：2 Text: 06, Conf: 0.9625216722488403
2025-03-31 17:15:27-0.33641600608825684-Region（(2198, 1926, 2275, 1984)）：4 Text: 34, Conf: 0.842035174369812
2025-03-31 17:15:27-0.33869314193725586-Region（(2332, 1916, 2416, 1987)）：5 Text: 82, Conf: 0.9974746704101562
2025-03-31 17:15:27-0.41469645500183105-Region（(739, 1529, 812, 1596)）：6 Text: 133, Conf: 0.9956898093223572
2025-03-31 17:15:27-0.2816200256347656-Region（(886, 1555, 972, 1625)）：7 Text: 195, Conf: 0.9957630634307861
2025-03-31 17:15:27-0.3099501132965088-Region（(598, 1552, 665, 1612)）：9 Text: 130, Conf: 0.9934964179992676
********** Process Time:1.8019309043884277 Rgions: 10-10 **********