From 631076f65bf9f2a039fca23073ddb6dc626fee07 Mon Sep 17 00:00:00 2001
From: bsw215583320 <baoshiwei121@163.com>
Date: 星期日, 27 四月 2025 15:41:51 +0800
Subject: [PATCH] refactor(herb_ai):优化图像识别和日志记录逻辑
---
openvino/herb_ai.py | 21 ++++++++++++---------
1 files changed, 12 insertions(+), 9 deletions(-)
diff --git a/openvino/herb_ai.py b/openvino/herb_ai.py
index 06734ff..81f9984 100644
--- a/openvino/herb_ai.py
+++ b/openvino/herb_ai.py
@@ -16,7 +16,6 @@
from logger_config import logger
import threading
-
multiprocessing.freeze_support()
@@ -95,7 +94,7 @@
logger.info(f"璇嗗埆缁撴灉杞崲涓轰繚瀛樺浘鐗囧悕绉�:, {save_name2}")
# 鍒ゆ柇鍥惧儚鐨勬竻鏅板害
# 淇濆瓨璋冩暣灏哄鍚庣殑鍥剧墖
- if laplacian > 200:
+ if laplacian > 150:
c_ = save_path + "2/c/"
if not os.path.exists(c_):
os.makedirs(c_)
@@ -223,8 +222,10 @@
det_res[class_name] = det_res[class_name] if det_res[class_name] > scores[i] else scores[i]
else:
det_res[class_name] = scores[i]
- print(det_res)
- logger.info(f"瀹夊叏妫�娴嬭瘑鍒粨鏋�, {det_res}")
+ # 濡傛灉det_res涓嶄负绌猴紝鍒欐墦鍗癲et_res
+ if det_res != {}:
+ print(det_res)
+ logger.info(f"瀹夊叏妫�娴嬭瘑鍒粨鏋�, {det_res}")
# 濡傛灉cass_ids涓寘鍚�0锛屽垯琛ㄧず鏈夊畨鍏ㄦ娴嬪埌浜轰綋
if 0 in class_ids:
res_ = "aidetect," + f"{det_res}"
@@ -246,8 +247,10 @@
else:
count += 1
class_old = class_
- print(f"{class_}:{count}: {max_probability}")
- logger.info(f"{class_}:{count}: {max_probability}")
+ if class_ == "shangliao":
+ print(f"{class_}:{count}: {max_probability}")
+ logger.info(f"{class_}:{count}: {max_probability}")
+
# 鍒ゆ柇鏄惁涓婃枡骞朵笖涓婃枡娆℃暟澶т簬10娆�
if class_ == "shangliao" and count > 10:
status = "姝ｅ湪涓婃枡"
@@ -283,9 +286,9 @@
predicted_class2 = np.argmax(probabilities2, axis=1)[0]
max_probability2 = np.max(probabilities2, axis=1)[0]
class_2 = hoister_position.class_names[predicted_class2]
- print(f"-----------{class_2}:{predicted_class2}: {max_probability2}")
- logger.info(f"-----------{class_2}:{predicted_class2}: {max_probability2}")
-
+ if class_2 == "high":
+ print(f"-----------{class_2}:{predicted_class2}: {max_probability2}")
+ logger.info(f"-----------{class_2}:{predicted_class2}: {max_probability2}")
if predicted_class2 == 0:
feeder_res = {class_2: max_probability2}
class_feeder = "aifeeder," + f"{feeder_res}"
--
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