How to implementation ONNX file for real time semantic segmentation using Deep Neural Network - opencv

Question

i have a problem in my code as shown in this code
import os
import cv2
import numpy as np
import matplotlib.pyplot as plt
labels = ['Background', 'Korosi', 'Tanah', 'Tanaman']
np.random.seed(42)
COLORS = np.random.randint(0, 255, size=(len(labels), 3), dtype="uint8")
net = cv2.dnn.readNetFromONNX('anomali_model1.onnx')
layer_names = net.getLayerNames()
output_layers = [layer_names[i - 1] for i in net.getUnconnectedOutLayers)]
capture = cv2.VideoCapture(0)
while True: re, img = capture.read()
#img = cv2.cvtColor(img, cv2.COLOR_RGBA2RGB)
#height, width, channels = img.shape
#blob = cv2.dnn.blobFromImage(img, 0.00392, (256, 256),
#swapRB=True, crop=False)
blob = cv2.dnn.blobFromImage(img, swapRB=True, crop=False)
net.setInput(blob)
outs = net.forward(output_layers)
class_ids = []
confidences = []
boxes = []
for out in outs:
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.5:
# Object detected
center_x = int(detection[0] * width)
center_y = int(detection[1] * height)
w = int(detection[2] * width)
h = int(detection[3] * height)
# Rectangle coordinates
x = int(center_x - w / 2)
y = int(center_y - h / 2)
boxes.append([x, y, w, h])
confidences.append(float(confidence))
class_ids.append(class_id)
indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
font = cv2.FONT_HERSHEY_PLAIN
colors = np.random.uniform(0, 255, size=(len(classes), 3))
for i in range(len(boxes)):
if i in indexes:
x, y, w, h = boxes[i]
label = str(classes[class_ids[i]])
color = colors[class_ids[i]]
cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)
cv2.putText(img, label, (x, y + 30), font, 2, color, 3)
cv2.imshow("Image",cv2.resize(img, (800,600)))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
And i get error like this:
error Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_10644\3517982312.py in <module>
9 blob = cv2.dnn.blobFromImage(img, swapRB=True, crop=False)
10 net.setInput(blob)
---> 11 outs = net.forward(output_layers)
12
13 class_ids = []
error: OpenCV(3.4.17) D:\a\opencv-python\opencv-python\opencv\modules\dnn\src\layers\convolution_layer.cpp:331: error: (-2:Unspecified error) Number of input channels should be multiple of 3 but got 640 in function 'cv::dnn::ConvolutionLayerImpl::getMemoryShapes'
can you help me to solve this problem? because I've looked into various sources but did not find a solution.
library version for this code
python version 3.7
tensorflow version 2.0
opencv version 3.4.17
I hope you all can solve this problem and share with me