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feat: 更新校准方法

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bmy
2024-06-05 16:07:32 +08:00
parent 4c1cf9ceb0
commit b787ce6ed0
6 changed files with 537 additions and 303 deletions
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122
utils.py
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@@ -1,6 +1,7 @@
from enum import Enum
import numpy as np
import erniebot
lane_error = 0
@@ -40,7 +41,7 @@ test1_resp = {
description: yolo 目标检测标签过滤器，需要传入连接到 yolo server 的 socket 对象
'''
class label_filter:
def __init__(self, socket, threshold=0.6):
def __init__(self, socket, threshold=0.5):
self.num = 0
self.pos = []
self.socket = socket
@@ -92,7 +93,7 @@ class label_filter:
return True, np.array(results)
return False, None
'''
description: 根据传入的标签过滤，返回该标签的个数以及 box
description: 根据传入的标签过滤，返回该标签的个数、box
param {*} self
param {*} tlabel
return {int, array}
@@ -107,34 +108,59 @@ class label_filter:
expect_boxes = (results[:, 0] == tlabel.value)
boxes = results[expect_boxes, :]
self.num = len(boxes)
self.pos = boxes[:, 2:] # [[x1 y1 x2 y2]]
return self.num, self.pos
return 0, []
if self.num:
self.pos = boxes[:, 2:] # [[x1 y1 x2 y2]]
return True, self.pos
return False, []
'''
description:
description: 仅限在岔路口判断方向牌处使用
param {*} self
param {*} tlabel_list
return {*}
'''
def get_mult(self, tlabel_list):
def get_mult_box(self, tlabel_list):
response = self.get_resp()
if response['code'] == 0:
ret, results = self.filter_box(response['data'])
target_counts = len(tlabel_list)
counts = 0
except_label = None
if ret:
for tlabel in tlabel_list:
expect_boxes = (results[:, 0] == tlabel.value)
has_true = np.any(expect_boxes)
if has_true:
counts += 1
else:
return False, []
if counts == target_counts:
return True, counts
return False, []
return False, []
return False, []
except_label = tlabel
box = results[expect_boxes, :][:, 2:][0]
error = (box[2] + box[0] - self.img_size[0]) / 2
break
if except_label != None:
return True, except_label, error
return False, None, None
return False, None, None
return False, None, None
def get_near_box(self, tlabel_list):
response = self.get_resp()
if response['code'] == 0:
ret, results = self.filter_box(response['data'])
except_label = []
abs_error_list = []
error_list = []
if ret:
for tlabel in tlabel_list:
expect_boxes = (results[:, 0] == tlabel.value)
has_true = np.any(expect_boxes)
if has_true:
except_label.append(tlabel)
box = results[expect_boxes, :][:, 2:][0]
error = (box[2] + box[0] - self.img_size[0]) / 2
abs_error_list.append(abs(error))
error_list.append(error)
if len(error_list) != 0:
abs_error_list = np.array(abs_error_list)
errormin_index = np.argmin(abs_error_list)
return True, except_label[errormin_index], error_list[errormin_index]
return False, None, None
return False, None, None
return False, None, None
'''
description: 判断传入的标签是否存在，存在返回 True
param {*} self
@@ -152,10 +178,10 @@ class label_filter:
return True
return False
'''
description: 根据传入的标签，
description: 根据传入的标签，寻找画面中最左侧的并返回 error
param {*} self
param {*} tlabel
return {*}
return {bool, error}
'''
def aim_left(self, tlabel):
# 如果标签存在，则返回列表中位置最靠左的目标框和中心的偏移值
@@ -181,12 +207,12 @@ class label_filter:
expect_boxes = (results[:, 0] == tlabel.value)
boxes = results[expect_boxes, :]
if len(boxes) == 0:
return (False, )
return (False, None)
xmax_values = boxes[:, 4] # xmax
xmax_index = np.argmax(xmax_values)
error = (boxes[xmax_index][4] + boxes[xmax_index][2] - self.img_size[0]) / 2
return (True, error)
return (False, )
return (False, None)
def aim_near(self, tlabel):
# 如果标签存在，则返回列表中位置最近的目标框和中心的偏移值
response = self.get_resp()
@@ -203,12 +229,47 @@ class label_filter:
return (True, error)
return (False, 0)
# class Calibrate:
# def __init__(self,by_cmd):
# # 车控制对象初始化
# self.by_cmd = by_cmd
# def aim(self,error):
# self.by_cmd.send_distance_x(error,)
class LLM:
def __init__(self):
erniebot.api_type = "qianfan"
erniebot.ak = "jReawMtWhPu0wrxN9Rp1MzZX"
erniebot.sk = "eowS1BqsNgD2i0C9xNnHUVOSNuAzVTh6"
self.model = 'ernie-3.5'
self.prompt = '''你是一个机器人动作规划者，需要把我的话翻译成机器人动作规划并生成对应的 json 结果，机器人工作空间参考右手坐标系。
严格按照下面的描述生成给定格式 json，从现在开始你仅仅给我返回 json 数据！'''
self.prompt += '''正确的示例如下：
向左移 0.1m, 向左转弯 85 度 [{'func': 'move', 'x': 0, 'y': 0.1},{'func': 'turn','angle': -85}],
向右移 0.2m, 向前 0.1m [{'func': 'move', 'x': 0, 'y': -0.2},{'func': 'move', 'x': 0.1, 'y': 0}],
向右转 85 度，向右移 0.1m [{'func': 'turn','angle': 85},{'func': 'move', 'x': 0, 'y': -0.1}],
原地左转 38 度 [{'func': 'turn','angle': -38}],
蜂鸣器发声 5 秒 [{'func': 'beep', 'time': 5}]
发光或者照亮 5 秒 [{'func': 'light', 'time': 5}]
'''
self.prompt += '''你无需回复我'''
self.messages = []
self.resp = None
self.reset()
def reset(self):
self.messages = [self.make_message(self.prompt)]
self.resp = erniebot.ChatCompletion.create(
model=self.model,
messages=self.messages,
)
self.messages.append(self.resp.to_message())
def make_message(self,content):
return {'role': 'user', 'content': content}
def get_command_json(self,chat):
self.messages.append(self.make_message(chat))
self.resp = erniebot.ChatCompletion.create(
model=self.model,
messages=self.messages,
)
self.messages.append(self.resp.to_message())
return self.resp.get_result()
if __name__ == '__main__':
@@ -222,4 +283,9 @@ if __name__ == '__main__':
print(obj.aim_left(tlabel.BBALL))
print(obj.aim_right(tlabel.BBALL))
print(obj.aim_near(tlabel.BBALL))
print(obj.get(tlabel.HOSPITAL))
print(obj.get(tlabel.HOSPITAL))
lmm_bot = LLM()
while True:
chat = input("输入：")
print(lmm_bot.get_command_json(chat))