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feat: 新增文心一言接口

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This commit is contained in:
bmy
2024-06-28 21:34:49 +08:00
parent 066ef112ad
commit e82c254dc4
5 changed files with 368 additions and 112 deletions
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227
test/test_filter.py
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@@ -9,6 +9,10 @@ from loguru import logger
from utils import tlabel
import zmq
import time
from by_cmd_py import by_cmd_py
import time
from utils import CountRecord
by_cmd = by_cmd_py()
context = zmq.Context()
socket = context.socket(zmq.REQ)
@@ -17,35 +21,210 @@ logger.info("subtask yolo client init")
filter = label_filter(socket)
filter.switch_camera(1)
offset = 12
while True:
time.sleep(0.2)
# ret1 = filter.get_mult(tlabel.RMARK)
# ret, label, error = filter.get_mult_box([tlabel.LMARK, tlabel.RMARK])
# if ret:
# # print(error)
# if abs(error) < 40:
# logger.info('yes')
label = tlabel.RBLOCK
def car_stop():
for _ in range(3):
by_cmd.send_speed_x(0)
time.sleep(0.2)
by_cmd.send_speed_omega(0)
# 蓝色球使用
def calibrate_right_new(label, offset, run = True, run_speed = 3.5):
not_found_counts = 0
ret, error = filter.aim_right(label)
while not ret:
not_found_counts += 1
if not_found_counts >= 20:
not_found_counts = 0
error = -320 # error > 0 front run
logger.info("calibrate_right_new:找不到次数超过 20 帧 直接前进寻找")
break
ret, error = filter.aim_right(label)
error += offset
if abs(error) > 10 and run:
if error > 0:
by_cmd.send_speed_x(-run_speed)
else:
by_cmd.send_speed_x(run_speed)
pass
# 停的位置已经很接近目标，可以直接使用 distance 校准
else:
# logger.info("停车时误差就小于")
# error = error * 3
# if error > 0:
# by_cmd.send_distance_x(-10, int(error))
# else:
# by_cmd.send_distance_x(10, int(-error))
return
while True:
ret, error = filter.aim_right(label)
while not ret:
ret, error = filter.aim_right(label)
error += offset
if ret:
if abs(error) <= 8:
car_stop()
logger.info("calibrate_right_new:行进时 误差小于 8 直接停车")
ret, error = filter.aim_right(label)
while not ret:
ret, error = filter.aim_right(label)
error += offset
logger.info(f"calibrate_right_new:停车后的误差是{error}")
if abs(error) > 8:
logger.info(f"calibrate_right_new:停车后的误差大于 8 使用 distance 校准")
error = error * 3
if error > 0:
by_cmd.send_distance_x(-10, int(error))
else:
by_cmd.send_distance_x(10, int(-error))
break
'''
description: 校准新方法 找到后停止 然后根据 error 判断前后低速前进 error < 5 后直接停车
如果停车后 error > 8 则使用 distance 校准
这个方法仅用于在视野里能找到的情况下进行校准，并不能实现边走边寻找 然后再校准
param {*} label
param {*} offset
param {*} run
param {*} run_speed
return {*}
'''
def calibrate_new(label, offset, run = True, run_speed = 3.5):
not_found_counts = 0
ret, box = filter.get(label)
while not ret:
# 注意这里一定要保证摄像头内有该目标 否则会无限循环
not_found_counts += 1
if not_found_counts >= 20:
not_found_counts = 0
error = -320 # error > 0 front run
logger.info("calibrate_new:找不到次数超过 20 帧 直接前进寻找")
ret, box = filter.get(label)
error = (box[0][2] + box[0][0] - 320) / 2 + offset
# ret, box = filter.get(tlabel.BBLOCK)
if ret:
print(error)
error = (box[0][2] + box[0][0] - 320) / 2 + offset
if abs(error) > 10 and run:
if error > 0:
by_cmd.send_speed_x(-run_speed)
else:
by_cmd.send_speed_x(run_speed)
# 停的位置已经很接近目标，可以直接使用 distance 校准
else:
pass
if abs(error) > 8:
logger.info(f"calibrate_new:停车后误差{error}大于 8 使用 distance 校准")
# error = error # 3
if error > 0:
by_cmd.send_distance_x(-10, int(error))
else:
by_cmd.send_distance_x(10, int(-error))
return
logger.info(f"calibrate_new:停车后误差{error}小于 8 不校准")
return
while True:
ret, box = filter.get(label)
while not ret:
ret, box = filter.get(label)
error = (box[0][2] + box[0][0] - 320) / 2 + offset
if ret:
if abs(error) <= 10: # 5
car_stop()
logger.info("calibrate_new:行进时 误差小于 10 直接停车")
ret, box = filter.get(label)
while not ret:
ret, box = filter.get(label)
error = (box[0][2] + box[0][0] - 320) / 2 + offset
logger.info(f"calibrate_new:停车后的误差是{error}")
if abs(error) > 8:
logger.info(f"calibrate_new:停车后的误差大于 8 使用 distance 校准")
error = error * 3
logger.error(f"error * 3{error}")
if error > 0:
by_cmd.send_distance_x(-10, int(error))
else:
by_cmd.send_distance_x(10, int(-error))
break
def explore_calibrate_new(label, offset, run_direc ,run_speed = 3.5):
# run_direc == 1 向前
if run_direc == 1:
by_cmd.send_speed_x(run_speed)
else:
by_cmd.send_speed_x(-run_speed)
while True:
ret, box = filter.get(label)
while not ret:
ret, box = filter.get(label)
error = (box[0][2] + box[0][0] - 320) / 2 + offset
if ret:
logger.info(f"当前误差:{error}, box[{box[0][2]},{box[0][0]}]")
# 校准速度越大 停车的条件越宽泛
if abs(error) <= 20:
car_stop()
logger.info("explore_calibrate_new:行进时 误差小于 10 直接停车")
error_sum = 0
for _ in range(3):
ret, box = filter.get(label)
while not ret:
ret, box = filter.get(label)
error = (box[0][2] + box[0][0] - 320) / 2 + offset
error_sum += error
error_sum /= 3
# logger.info(f"停车后像素误差:{error}")
logger.info(f"停车后像素误差:{error_sum}")
# if abs(error) > 8:
logger.info(f"explore_calibrate_new:停车后的误差大于 8 使用 distance 校准")
error_sum = error_sum * 3
logger.error(f"error * 3 {error}")
if error > 0:
by_cmd.send_distance_x(-10, int(error))
else:
by_cmd.send_distance_x(10, int(-error))
break
offset = 10
# by_cmd.send_angle_claw_arm(217)
# while True:
# pass
# while (by_cmd.send_angle_camera(180) == -1):
# by_cmd.send_angle_camera(180)
while (by_cmd.send_angle_camera(180) == -1):
by_cmd.send_angle_camera(180)
# by_cmd.send_speed_x(15)
find_counts = 0
label = tlabel.HOSPITAL
record = CountRecord(5)
while True:
time.sleep(0.2)
# ret = filter.find(label)
# ret = filter.find(label)
# if ret > 0:
# find_counts += 1
# if record(label):
# car_stop()
# if find_counts >= 5:
# car_stop()
ret, box = filter.get(label)
while not ret:
ret, box = filter.get(label)
width = box[0][2] - box[0][0]
logger.info(width)
# error = (box[0][2] + box[0][0] - 320) / 2 + offset
# explore_calibrate_new(tlabel.LPILLER, offset = 10, run_direc = 1, run_speed = 5)
# calibrate_new(label, offset = 15, run = True)
# car_stop()
# time.sleep(0.5)
# for _ in range(3):
# calibrate_right_new(tlabel.BBALL, offset = 27, run = True, run_speed = 4)
# logger.info("抓蓝色球")
# time.sleep(5)
# logger.info("抓取块")
# time.sleep(0.1)
# if ret1:
# print(error1)
# if abs(error1) < 30:
# print("you")
# elif ret2:
# print(error2)
# if abs(error2) < 30:
# print("zuo")

8
test/test_llm.py
View File

@@ -14,7 +14,7 @@ class LLM:
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！'''
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}],
@@ -22,6 +22,8 @@ class LLM:
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}]
向右走 30cm，照亮 2s [{'func': 'move', 'x': 0, 'y': -0.3}, {'func': 'light', 'time': 2}],
向左移 0.2m, 向后 0.1m [{'func': 'move', 'x': 0, 'y': 0.2},{'func': 'move', 'x': -0.1, 'y': 0}],
'''
self.messages = []
self.resp = None
@@ -47,6 +49,8 @@ if __name__ == "__main__":
lmm_bot = LLM()
while True:
chat = input("输入：")
print(lmm_bot.get_command_json(chat))
resp = lmm_bot.get_command_json(chat).replace(' ', '').replace('\n', '').replace('\t', '')
print(eval(resp[7:-3]))