NanjingForestryUniversity/supermachine--tomato-passion_fruit
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feat:增加百香果空果拖判断逻辑（如果直径为0，则糖度值也为0，即返回全0数据）；添加尺寸转换，现在所有的返回数据均为显示尺寸单位数值（糖度值*1000，绿色占比*100，缺陷面积*100进行数据传输）

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TG 2024-06-23 23:26:50 +08:00
parent b0cf31fd60
commit f4ce2fa789
4 changed files with 37 additions and 29 deletions
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25
20240529RGBtest3/classifer.py
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@ -417,6 +417,7 @@ class Data_processing:
# 初始化统计数据 # 初始化统计数据
count_black_areas = 0 count_black_areas = 0
total_pixels_black_areas = 0 total_pixels_black_areas = 0
s = 0.00021973702422145334
# 对于每个白色区域，查找内部的黑色小区域 # 对于每个白色区域，查找内部的黑色小区域
for contour in contours_white: for contour in contours_white:
@ -436,7 +437,7 @@ class Data_processing:
total_pixels_black_areas += cv2.contourArea(c) total_pixels_black_areas += cv2.contourArea(c)
number_defects = count_black_areas number_defects = count_black_areas
total_pixels = total_pixels_black_areas total_pixels = total_pixels_black_areas * s
return number_defects, total_pixels return number_defects, total_pixels
def weight_estimates(self, long_axis, short_axis): def weight_estimates(self, long_axis, short_axis):
@ -451,11 +452,12 @@ class Data_processing:
float: 估算的西红柿体积 float: 估算的西红柿体积
""" """
density = 0.652228972 density = 0.652228972
a = ((long_axis / 535) * 6.3) / 2 a = ((long_axis / 425) * 6.3) / 2
b = ((short_axis /535) * 6.3) / 2 b = ((short_axis / 425) * 6.3) / 2
volume = 4 / 3 * np.pi * a * b * b volume = 4 / 3 * np.pi * a * b * b
weigth = round(volume * density) weight = round(volume * density)
return weigth #重量单位为g
return weight
def analyze_tomato(self, img): def analyze_tomato(self, img):
""" """
分析给定图像，提取和返回西红柿的长径、短径、缺陷数量和缺陷总面积，并返回处理后的图像。 分析给定图像，提取和返回西红柿的长径、短径、缺陷数量和缺陷总面积，并返回处理后的图像。
@ -490,8 +492,10 @@ class Data_processing:
number_defects, total_pixels = self.analyze_defect(new_bin_img) number_defects, total_pixels = self.analyze_defect(new_bin_img)
# 将处理后的图像转换为 RGB 格式 # 将处理后的图像转换为 RGB 格式
rp = cv2.cvtColor(org_defect, cv2.COLOR_BGR2RGB) rp = cv2.cvtColor(org_defect, cv2.COLOR_BGR2RGB)
diameter = (long_axis + short_axis) / 2 #直径单位为cm，所以需要除以10
if diameter < 200: diameter = (long_axis + short_axis) /425 * 63 / 2 / 10
# 如果直径小于3，判断为空果拖异常图，则将所有值重置为0
if diameter < 3:
diameter = 0 diameter = 0
green_percentage = 0 green_percentage = 0
number_defects = 0 number_defects = 0
@ -515,14 +519,15 @@ class Data_processing:
max_mask = pf.find_largest_component(combined_mask) max_mask = pf.find_largest_component(combined_mask)
contour_mask = self.contour_process(max_mask) contour_mask = self.contour_process(max_mask)
long_axis, short_axis = self.analyze_ellipse(contour_mask) long_axis, short_axis = self.analyze_ellipse(contour_mask)
weigth = self.weight_estimates(long_axis, short_axis) weight = self.weight_estimates(long_axis, short_axis)
number_defects, total_pixels = self.analyze_defect(max_mask) number_defects, total_pixels = self.analyze_defect(max_mask)
edge = pf.draw_contours_on_image(img, contour_mask) edge = pf.draw_contours_on_image(img, contour_mask)
org_defect = pf.bitwise_and_rgb_with_binary(edge, max_mask) org_defect = pf.bitwise_and_rgb_with_binary(edge, max_mask)
rp = cv2.cvtColor(org_defect, cv2.COLOR_BGR2RGB) rp = cv2.cvtColor(org_defect, cv2.COLOR_BGR2RGB)
diameter = (long_axis + short_axis) / 2 #直径单位为cm，所以需要除以10
diameter = (long_axis + short_axis) /425 * 63 / 2 / 10
return diameter, weigth, number_defects, total_pixels, rp return diameter, weight, number_defects, total_pixels, rp
# #下面封装的是ResNet18和ResNet34的网络模型构建 # #下面封装的是ResNet18和ResNet34的网络模型构建

12
20240529RGBtest3/main.py
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@ -46,14 +46,14 @@ def process_data(cmd: str, images: list, spec: any, dp: Data_processing, pipe: P
elif cmd == 'PF': elif cmd == 'PF':
# 百香果 # 百香果
diameter, weigth, number_defects, total_pixels, rp = dp.analyze_passion_fruit(img) diameter, weight, number_defects, total_pixels, rp = dp.analyze_passion_fruit(img)
if i <= 2: if i <= 2:
diameter_axis_list.append(diameter) diameter_axis_list.append(diameter)
max_defect_num = max(max_defect_num, number_defects) max_defect_num = max(max_defect_num, number_defects)
max_total_defect_area = max(max_total_defect_area, total_pixels) max_total_defect_area = max(max_total_defect_area, total_pixels)
if i == 1: if i == 1:
rp_result = rp rp_result = rp
weigth = weigth weight = weight
else: else:
logging.error(f'错误指令，指令为{cmd}') logging.error(f'错误指令，指令为{cmd}')
@ -63,14 +63,16 @@ def process_data(cmd: str, images: list, spec: any, dp: Data_processing, pipe: P
if cmd == 'TO': if cmd == 'TO':
brix = 0 brix = 0
weigth = 0 weight = 0
response = pipe.send_data(cmd=cmd, brix=brix, diameter=diameter, green_percentage=gp, weigth=weigth, response = pipe.send_data(cmd=cmd, brix=brix, diameter=diameter, green_percentage=gp, weight=weight,
defect_num=max_defect_num, total_defect_area=max_total_defect_area, rp=rp_result) defect_num=max_defect_num, total_defect_area=max_total_defect_area, rp=rp_result)
return response return response
elif cmd == 'PF': elif cmd == 'PF':
green_percentage = 0 green_percentage = 0
brix = detector.predict(spec) brix = detector.predict(spec)
response = pipe.send_data(cmd=cmd, brix=brix, green_percentage=green_percentage, diameter=diameter, weigth=weigth, if diameter == 0:
brix = 0
response = pipe.send_data(cmd=cmd, brix=brix, green_percentage=green_percentage, diameter=diameter, weight=weight,
defect_num=max_defect_num, total_defect_area=max_total_defect_area, rp=rp_result) defect_num=max_defect_num, total_defect_area=max_total_defect_area, rp=rp_result)
return response return response

8
20240529RGBtest3/qt_test.py
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@ -150,17 +150,17 @@ class MainWindow(QMainWindow):
# 解析数据 # 解析数据
cmd_result = data[:2].decode('ascii').strip().upper() cmd_result = data[:2].decode('ascii').strip().upper()
brix = (int.from_bytes(data[2:4], byteorder='big')) / 1000 brix = (int.from_bytes(data[2:4], byteorder='big')) / 1000
green_percentage = int.from_bytes(data[4:5], byteorder='big') green_percentage = (int.from_bytes(data[4:5], byteorder='big')) / 100
diameter = int.from_bytes(data[5:7], byteorder='big') diameter = int.from_bytes(data[5:7], byteorder='big')
weight = int.from_bytes(data[7:8], byteorder='big') weight = int.from_bytes(data[7:8], byteorder='big')
defect_num = int.from_bytes(data[8:10], byteorder='big') defect_num = int.from_bytes(data[8:10], byteorder='big')
total_defect_area = int.from_bytes(data[10:14], byteorder='big') total_defect_area = (int.from_bytes(data[10:14], byteorder='big')) / 100
heigth = int.from_bytes(data[14:16], byteorder='big') heigth = int.from_bytes(data[14:16], byteorder='big')
width = int.from_bytes(data[16:18], byteorder='big') width = int.from_bytes(data[16:18], byteorder='big')
rp = data[18:] rp = data[18:]
img = np.frombuffer(rp, dtype=np.uint8).reshape(heigth, width, -1) img = np.frombuffer(rp, dtype=np.uint8).reshape(heigth, width, -1)
print(f"指令:{cmd_result}, 糖度值:{brix}, 绿色占比:{green_percentage}, 直径:{diameter}, " print(f"指令:{cmd_result}, 糖度值:{brix}, 绿色占比:{green_percentage}, 直径:{diameter}cm, "
f"预估重量:{weight}, 缺陷个数:{defect_num}, 缺陷面积:{total_defect_area}, 结果图的尺寸:{img.shape}") f"预估重量:{weight}g, 缺陷个数:{defect_num}, 缺陷面积:{total_defect_area}cm^2, 结果图的尺寸:{img.shape}")
# 显示结果图像 # 显示结果图像

21
20240529RGBtest3/utils.py
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@ -159,13 +159,13 @@ class Pipe:
spec = np.frombuffer(spec, dtype=np.uint16).reshape((n_rows, n_bands, -1)).transpose(0, 2, 1) spec = np.frombuffer(spec, dtype=np.uint16).reshape((n_rows, n_bands, -1)).transpose(0, 2, 1)
return cmd, spec return cmd, spec
def send_data(self,cmd:str, brix, green_percentage, weigth, diameter, defect_num, total_defect_area, rp): def send_data(self,cmd:str, brix, green_percentage, weight, diameter, defect_num, total_defect_area, rp):
''' '''
发送数据 发送数据
:param cmd: :param cmd:
:param brix: :param brix:
:param green_percentage: :param green_percentage:
:param weigth: :param weight:
:param diameter: :param diameter:
:param defect_num: :param defect_num:
:param total_defect_area: :param total_defect_area:
@ -195,6 +195,7 @@ class Pipe:
img_bytes = img.tobytes() img_bytes = img.tobytes()
diameter = diameter.to_bytes(2, byteorder='big') diameter = diameter.to_bytes(2, byteorder='big')
defect_num = defect_num.to_bytes(2, byteorder='big') defect_num = defect_num.to_bytes(2, byteorder='big')
total_defect_area = total_defect_area * 1000
total_defect_area = int(total_defect_area).to_bytes(4, byteorder='big') total_defect_area = int(total_defect_area).to_bytes(4, byteorder='big')
length = len(img_bytes) + 18 length = len(img_bytes) + 18
length = length.to_bytes(4, byteorder='big') length = length.to_bytes(4, byteorder='big')
@ -202,22 +203,22 @@ class Pipe:
brix = 0 brix = 0
brix = brix.to_bytes(2, byteorder='big') brix = brix.to_bytes(2, byteorder='big')
gp = green_percentage.to_bytes(1, byteorder='big') gp = green_percentage.to_bytes(1, byteorder='big')
weigth = 0 weight = 0
weigth = weigth.to_bytes(1, byteorder='big') weight = weight.to_bytes(1, byteorder='big')
send_message = length + cmd_re + brix + gp + diameter + weigth + defect_num + total_defect_area + height + width + img_bytes send_message = length + cmd_re + brix + gp + diameter + weight + defect_num + total_defect_area + height + width + img_bytes
elif cmd == 'PF': elif cmd == 'PF':
brix = int(brix * 1000).to_bytes(2, byteorder='big') brix = int(brix * 1000).to_bytes(2, byteorder='big')
gp = 0 gp = 0
gp = gp.to_bytes(1, byteorder='big') gp = gp.to_bytes(1, byteorder='big')
weigth = weigth.to_bytes(1, byteorder='big') weight = weight.to_bytes(1, byteorder='big')
send_message = length + cmd_re + brix + gp + diameter + weigth + defect_num + total_defect_area + height + width + img_bytes send_message = length + cmd_re + brix + gp + diameter + weight + defect_num + total_defect_area + height + width + img_bytes
elif cmd == 'KO': elif cmd == 'KO':
brix = 0 brix = 0
brix = brix.to_bytes(2, byteorder='big') brix = brix.to_bytes(2, byteorder='big')
gp = 0 gp = 0
gp = gp.to_bytes(1, byteorder='big') gp = gp.to_bytes(1, byteorder='big')
weigth = 0 weight = 0
weigth = weigth.to_bytes(1, byteorder='big') weight = weight.to_bytes(1, byteorder='big')
defect_num = 0 defect_num = 0
defect_num = defect_num.to_bytes(2, byteorder='big') defect_num = defect_num.to_bytes(2, byteorder='big')
total_defect_area = 0 total_defect_area = 0
@ -228,7 +229,7 @@ class Pipe:
width = width.to_bytes(2, byteorder='big') width = width.to_bytes(2, byteorder='big')
img_bytes = np.zeros((100, 100, 3), dtype=np.uint8).tobytes() img_bytes = np.zeros((100, 100, 3), dtype=np.uint8).tobytes()
length = (18).to_bytes(4, byteorder='big') length = (18).to_bytes(4, byteorder='big')
send_message = length + cmd_re + brix + gp + diameter + weigth + defect_num + total_defect_area + height + width + img_bytes send_message = length + cmd_re + brix + gp + diameter + weight + defect_num + total_defect_area + height + width + img_bytes
try: try:
win32file.WriteFile(self.rgb_send, send_message) win32file.WriteFile(self.rgb_send, send_message)
# time.sleep(0.01) # time.sleep(0.01)