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fix: rm yolo

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This commit is contained in:
linyimin
2026-06-04 09:00:10 +08:00
parent c46cf5c567
commit 1a0bfd54f7
6 changed files with 17 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
app.yaml
View File

@@ -1,6 +1,6 @@
id: t11
name: t11
version: 2.15.6
version: 2.15.8
author: t11
icon: ''
desc: t11

2
config.py
View File

@@ -260,7 +260,7 @@ TRIANGLE_SAMPLE_RADIUS_CM = 15.0
TRIANGLE_SAMPLE_ANGLES_DEG = (0, 90, 180, 270)
TRIANGLE_SAMPLE_PATCH_HALF_PX = 2
# 开机阶段预加载 YOLO detector；detect 使用 dual_buff=False，避免返回上一帧结果。
TRIANGLE_YOLO_PRELOAD_ON_BOOT = True
TRIANGLE_YOLO_PRELOAD_ON_BOOT = False
# ── 第二段 YOLO：仅在 Stage1 裁切出的靶环图上推理（与合成 stage2 训练数据一致）→ 子框内传统算法取直角点 ──
# Stage1 靶环裁切内如何找黑三角标记（对比耗时时可切换）：

14
test/test_decect.py
View File

@@ -71,8 +71,8 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
# -- 3. 红色掩码：在循环外只算一次
mask_red = cv2.bitwise_or(
cv2.inRange(hsv, np.array([0, 80, 0]), np.array([10, 255, 255])),
cv2.inRange(hsv, np.array([170, 80, 0]), np.array([180, 255, 255])),
cv2.inRange(hsv, np.array([0, 50, 40]), np.array([10, 255, 255])),
cv2.inRange(hsv, np.array([170, 50, 40]), np.array([180, 255, 255])),
)
kernel_red = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_CLOSE, kernel_red)
@@ -81,10 +81,10 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
red_candidates = []
for cnt_r in contours_red:
ar = cv2.contourArea(cnt_r)
if ar <= 50:
if ar <= 30:
continue
pr = cv2.arcLength(cnt_r, True)
if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.6:
if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.4:
continue
if len(cnt_r) >= 5:
(xr, yr), (wr, hr), _ = cv2.fitEllipse(cnt_r)
@@ -125,7 +125,7 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
ddx = yellow_center[0] - rc["center"][0]
ddy = yellow_center[1] - rc["center"][1]
dist_centers = math.hypot(ddx, ddy)
if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.8:
if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.7:
print(f"[target] -> 找到匹配的红圈: 黄心({yellow_center}), "
f"红心({rc['center']}), 距离:{dist_centers:.1f}, "
f"黄半径:{yellow_radius}, 红半径:{rc['radius']}")
@@ -279,8 +279,8 @@ def run_offline_test(image_path):
result_img.draw_string(0, 0, info_str, color=color_black, scale=1.0)
# 5. 保存结果图片
output_path = image_path.replace(".bmp", "_result.bmp")
output_path = image_path.replace(".jpg", "_result.jpg")
base, ext = os.path.splitext(image_path)
output_path = f"{base}_result{ext}"
try:
result_img.save(output_path, quality=100)
print(f"[SUCCESS] 结果已保存至: {output_path}")

2
version.md
View File

@@ -17,3 +17,5 @@
# 2.15.4 更新版本号
# 2.15.5 打印ota进度
# 2.15.6 更新版本号
# 2.15.7 更新版本号
# 2.15.8 启动不加载预加载yolo

2
version.py
View File

@@ -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 = '2.15.6'
VERSION = '2.15.7'

10
vision.py
View File

@@ -570,8 +570,8 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
# -- 3. 红色掩码：在循环外只算一次
mask_red = cv2.bitwise_or(
cv2.inRange(hsv, np.array([0, 80, 0]), np.array([10, 255, 255])),
cv2.inRange(hsv, np.array([170, 80, 0]), np.array([180, 255, 255])),
cv2.inRange(hsv, np.array([0, 50, 40]), np.array([10, 255, 255])),
cv2.inRange(hsv, np.array([170, 50, 40]), np.array([180, 255, 255])),
)
kernel_red = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_CLOSE, kernel_red)
@@ -580,10 +580,10 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
red_candidates = []
for cnt_r in contours_red:
ar = cv2.contourArea(cnt_r)
if ar <= 50:
if ar <= 30:
continue
pr = cv2.arcLength(cnt_r, True)
if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.6:
if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.4:
continue
if len(cnt_r) >= 5:
(xr, yr), (wr, hr), _ = cv2.fitEllipse(cnt_r)
@@ -625,7 +625,7 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
ddx = yellow_center[0] - rc["center"][0]
ddy = yellow_center[1] - rc["center"][1]
dist_centers = math.hypot(ddx, ddy)
if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.8:
if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.7:
if logger:
logger.info(f"[target] -> 找到匹配的红圈: 黄心({yellow_center}), "
f"红心({rc['center']}), 距离:{dist_centers:.1f}, "