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feat: 2.17.18

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linyimin
2026-09-23 11:03:15 +08:00
parent e67c410325
commit 2834f5b9b7
6 changed files with 39 additions and 42 deletions
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app.yaml
+1 -1
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@@ -1,6 +1,6 @@
id: t11
name: t11
version: 2.17.15
version: 2.17.18
author: t11
icon: ''
desc: t11
camera_manager.py
+1 -26
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@@ -8,15 +8,6 @@ import threading
import config
from logger_manager import logger_manager
_USE_CV = False
try:
import cv2
import numpy as np
from maix import image as _maix_image
_USE_CV = True
except ImportError:
pass
class CameraManager:
"""相机管理器（单例）"""
@@ -110,23 +101,7 @@ class CameraManager:
with self._camera_lock:
if self._camera is None:
self.init_camera()
frame = self._camera.read()
if frame is not None and _USE_CV:
try:
v_flip = getattr(config, 'CAMERA_V_FLIP', False)
h_mirror = getattr(config, 'CAMERA_H_MIRROR', False)
if v_flip or h_mirror:
img_cv = _maix_image.image2cv(frame, False, False)
if v_flip and h_mirror:
img_cv = cv2.flip(img_cv, -1)
elif v_flip:
img_cv = cv2.flip(img_cv, 0)
elif h_mirror:
img_cv = cv2.flip(img_cv, 1)
frame = _maix_image.cv2image(img_cv, False, False)
except Exception:
pass
return frame
return self._camera.read()
def show(self, image):
"""
config.py
+3 -5
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@@ -15,8 +15,6 @@ LOCAL_FILENAME = APP_DIR + "/main_tmp.py"
# 相机初始化分辨率（CameraManager / main.py 使用）
CAMERA_WIDTH = 640
CAMERA_HEIGHT = 480
CAMERA_V_FLIP = True # 摄像头垂直翻转（上下颠倒时设为 True）
CAMERA_H_MIRROR = True # 摄像头水平镜像（左右反了时设为 True）
# 三角形检测缩图比例：默认按相机最长边缩到 1/2（性能更稳；可按需调整）
# 取值范围建议 (0.25 ~ 1.0]；1.0 表示不缩图
@@ -329,16 +327,16 @@ MAX_CMD_THREADS = 10 # 并发命令线程上限（防止服务器下
# ==================== 图像保存配置 ====================
SAVE_IMAGE_ENABLED = True # 是否保存图像（True=保存，False=不保存）
SAVE_IMAGE_ON_FAILURE = False # 检测失败时是否强制保存图像（供调试测试用）
SAVE_IMAGE_ON_FAILURE = True # 检测失败时是否强制保存图像（供调试测试用）
PHOTO_DIR = "/root/phot" # 照片存储目录
MAX_IMAGES = 1000
SAVE_RAW_IMAGE_ENABLED = True # 额外保存完整原始帧（不画框、不画点、不裁剪）
SAVE_RAW_IMAGE_ENABLED = False # 额外保存完整原始帧（不画框、不画点、不裁剪）
RAW_IMAGE_DIR = PHOTO_DIR + "/raw"
RAW_IMAGE_MAX_IMAGES = MAX_IMAGES
# Stage2 调试目录（默认 PHOTO_DIR/stage2_roi）内 JPEG 最多保留张数；None 表示与 MAX_IMAGES 相同
TRIANGLE_BLACK_YOLO_STAGE2_ROI_MAX_IMAGES = None
SHOW_CAMERA_PHOTO_WHILE_SHOOTING = True # 是否在拍摄时显示摄像头图像（True=显示，False=不显示），建议在连着USB测试过程中打开
SHOW_CAMERA_PHOTO_WHILE_SHOOTING = False # 是否在拍摄时显示摄像头图像（True=显示，False=不显示），建议在连着USB测试过程中打开
# ==================== OTA配置 ====================
MAX_BACKUPS = 5
main.py
+2 -2
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@@ -385,11 +385,11 @@ def cmd_str():
pressure_max = adc_val
if len(pressure_buf) >= PRESSURE_BATCH_SIZE:
_flush_pressure_buf("batch")
# 突变增量检测：压力增量大于300时触发
# 突变增量检测：压力增量大于400时触发
# 触发后需等气压降到触发值以下才重新检测增量
if adc_val < trigger_adc_val :
enable_check = True
if (adc_val - last_adc_val) > 500 and enable_check:
if (adc_val - last_adc_val) > 200 and enable_check:
hardware_manager.start_idle_timer() # 重新计时
last_adc_trigger = current_time
trigger_adc_val = adc_val # 记录触发时的气压值
shoot_manager.py
+31 -7
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@@ -59,6 +59,7 @@ def analyze_shot(frame, laser_point=None):
"""
logger = logger_manager.logger
from datetime import datetime
yellow_algorithm_ms = 0.0
# ── Step 1: 确定激光点 ────────────────────────────────────────────────────
laser_point_method = None
@@ -74,7 +75,11 @@ def analyze_shot(frame, laser_point=None):
logger.info(f"[算法] 使用校准值: {laser_manager.laser_point}")
else:
# 动态模式：先做一次无激光点检测以估算距离，再推算激光点
_, _, _, _, best_radius1_temp, _ = detect_circle_v3(frame, None)
_t_yellow = time_std.perf_counter()
try:
_, _, _, _, best_radius1_temp, _ = detect_circle_v3(frame, None)
finally:
yellow_algorithm_ms += (time_std.perf_counter() - _t_yellow) * 1000.0
distance_m_first = estimate_distance(best_radius1_temp) if best_radius1_temp else None
if distance_m_first and distance_m_first > 0:
laser_point = laser_manager.calculate_laser_point_from_distance(distance_m_first)
@@ -119,6 +124,7 @@ def analyze_shot(frame, laser_point=None):
"laser_point": laser_point, "laser_point_method": laser_point_method,
"offset_method": "yellow_ellipse" if ellipse_params else "yellow_circle",
"distance_method": "yellow_radius",
"yellow_algorithm_ms": float(yellow_algorithm_ms),
}
if yolo_roi_xyxy is not None:
out["yolo_roi_xyxy"] = yolo_roi_xyxy
@@ -126,9 +132,12 @@ def analyze_shot(frame, laser_point=None):
if not use_tri:
# 三角形未配置，直接跑圆形检测
return _build_circle_result(
detect_circle_v3(frame, laser_point, img_cv=img_cv)
)
_t_yellow = time_std.perf_counter()
try:
cdata = detect_circle_v3(frame, laser_point, img_cv=img_cv)
finally:
yellow_algorithm_ms += (time_std.perf_counter() - _t_yellow) * 1000.0
return _build_circle_result(cdata)
# ── Step 4: 先独占跑三角形，超时或失败后再跑圆形（不与圆心并行，避免抢 CPU）──
roi_xyxy = None
@@ -281,6 +290,7 @@ def analyze_shot(frame, laser_point=None):
"laser_point": laser_point, "laser_point_method": laser_point_method,
"offset_method": tri.get("offset_method") or "triangle_homography",
"distance_method": tri.get("distance_method") or "pnp_triangle",
"yellow_algorithm_ms": float(yellow_algorithm_ms),
"tri_markers": tri.get("markers", []),
"tri_markers_completed": tri.get("markers_completed", []),
"tri_homography": tri.get("homography"),
@@ -301,7 +311,11 @@ def analyze_shot(frame, laser_point=None):
# 三角形超时或失败 → 跑圆心；圆心跑完后再检查三角形是否已结束
try:
cdata = detect_circle_v3(frame, laser_point, img_cv=img_cv)
_t_yellow = time_std.perf_counter()
try:
cdata = detect_circle_v3(frame, laser_point, img_cv=img_cv)
finally:
yellow_algorithm_ms += (time_std.perf_counter() - _t_yellow) * 1000.0
except Exception as e:
logger.error(f"[CIRCLE] 圆形检测异常: {e}")
cdata = (frame, None, None, None, None, None)
@@ -337,10 +351,15 @@ def process_shot(adc_val):
# Classify only the current shot frame; never reuse a previous result.
target_class_result = None
yolo_target_ms = 0.0
try:
from target_roi_yolo import try_get_target_class_from_yolo
target_class_result = try_get_target_class_from_yolo(frame, logger=logger)
_t_yolo_target = time_std.perf_counter()
try:
target_class_result = try_get_target_class_from_yolo(frame, logger=logger)
finally:
yolo_target_ms = (time_std.perf_counter() - _t_yolo_target) * 1000.0
if logger:
logger.info(f"[YOLO-TARGET] 当前箭业务结果: {target_class_result}")
except Exception as exc:
@@ -370,6 +389,7 @@ def process_shot(adc_val):
laser_point_method = analysis_result["laser_point_method"]
offset_method = analysis_result.get("offset_method", "yellow_circle")
distance_method = analysis_result.get("distance_method", "yellow_radius")
yellow_algorithm_ms = float(analysis_result.get("yellow_algorithm_ms", 0.0) or 0.0)
tri_markers = analysis_result.get("tri_markers", [])
tri_markers_completed = analysis_result.get("tri_markers_completed", [])
tri_homography = analysis_result.get("tri_homography")
@@ -419,7 +439,9 @@ def process_shot(adc_val):
"r": 20.0, # 保留字段（服务端当前忽略，物理外环半径 cm）
"target_class": target_label,
"target_class_confidence": (
float(target_confidence) if target_confidence is not None else None
round(float(target_confidence), 2)
if target_confidence is not None
else None
),
"d": round((distance_m or 0.0) * 100),
"d_laser": round((laser_distance_m or 0.0) * 100),
@@ -431,6 +453,8 @@ def process_shot(adc_val):
"target_y": float(y),
"offset_method": offset_method,
"distance_method": distance_method,
"yellow_algorithm_ms": round(yellow_algorithm_ms, 2),
"yolo_target_ms": round(float(yolo_target_ms), 2),
}
if ellipse_params:
version.py
+1 -1
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@@ -4,6 +4,6 @@
应用版本号
每次 OTA 更新时，只需要更新这个文件中的版本号
"""
VERSION = '2.17.15'
VERSION = '2.17.18'