asmorkalov
commented
1 year ago "but the kernel restart when compiling..." - what does it mean? Do you mean build failure or run-time network inference issue?
Open IltonWhatever opened 1 year ago
asmorkalov
commented
1 year ago "but the kernel restart when compiling..." - what does it mean? Do you mean build failure or run-time network inference issue?
IltonWhatever
commented
1 year ago in the execution of the code the kernel restarts
IltonWhatever
commented
1 year ago 
IltonWhatever
commented
1 year ago This happens when I use this in code: net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA) net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)
asmorkalov
commented
1 year ago Please provide complete code reproducer and the model.
IltonWhatever
commented
1 year ago import time import cv2
CONFIDENCE_THRESHHOLD = 0.6 NMS_THRESHOLD = 0.6 COLORS = [(0, 255, 255), (255, 255, 0), (0, 255, 0), (255, 0, 0)] txt = [0,0,0] # Text color
class_name = [] with open('coco.names','r') as f: class_names = [cname.strip() for cname in f.readlines()]
net = cv2.dnn.readNet('yolov4-tiny.weights', 'yolov4-tiny.cfg')
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA) net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)
model = cv2.dnn_DetectionModel(net) model.setInputParams(size=(416, 416), scale=1/255)
#Use 0 to use webcam or put the path of a video between its extension''
#Example: cap = cv2.VideoCapture('videoplayback.mp4')cap = cv2.VideoCapture('videoplayback.mp4')
prev_frame = 0 # Previous frame, used to calculate FPS start = 0 while True:
# Frame capture
_, frame = cap.read()
# Window Size
#frame = cv2.resize(frame, (1080, 780))
# Start of MS count
start = time.time()
# detection
classes, scores, boxes = model.detect(frame, CONFIDENCE_THRESHHOLD, NMS_THRESHOLD)
# End of MS Count
end = time.time()
# Cycle through all detections
for (classid, score, box) in zip(classes, scores, boxes):
# Generating colors for classes
color = COLORS[int(classid) % len(COLORS)]
txt = tuple(txt)
# Getting the class name by ID and its Score
label = f'{class_names[classid]} : {int(score*100)}%'
# Drawing the detection box
cv2.rectangle(frame, box, color, 1)
# Writing the class name on top of the object box
cv2.putText(frame, label, (box[0], box[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, txt, 3) # Colored
cv2.putText(frame, label, (box[0], box[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 1) # Black part
# Calculating the time it took to make the detection
#FPS
fps_label = 1/(start-prev_frame)
prev_frame = start
fps_label = int(fps_label)
fps_label = str(fps_label)
# Writing the FPS on the Image
cv2.putText(frame, fps_label, (0, 25), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0 , 0), 5)
cv2.putText(frame, fps_label, (0, 25), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255 , 0), 3)
# Creating the window
cv2.imshow('detections', frame)
# Pressing Q on the keyboard at any time to close the program
if cv2.waitKey(1) & 0xFF == ord('q'):
breakcap.release() cv2.destroyAllWindows()
asmorkalov
commented
1 year ago Could you attach the model too or, if it's confidential, attach the same model with random (zero) weights?
IltonWhatever
commented
1 year ago Model is "Yolo" Yolo Model.zip
asmorkalov
commented
1 year ago Thanks for the model. The model is loaded by model diagnostic tool without issues. Most probably it's CUDNN/CUDA specific issue.
IltonWhatever
commented
1 year ago did the code work using CUDA ?
zihaomu
commented
1 year ago Hi @WanliZhong, please take a look.
WanliZhong
commented
1 year ago @IltonWhatever Hi, I think you can try to downgrade the VS or CUDA version due to compatibility issues. I get the table below from the link https://quasar.ugent.be/files/doc/cuda-msvc-compatibility.html
IltonWhatever
commented
1 year ago @IltonWhateverOi, acho que você pode tentar fazer o downgrade da versão VS ou CUDA devido a problemas de compatibilidade. Eu recebo a tabela abaixo do link https://quasar.ugent.be/files/doc/cuda-msvc-compatibility.html
Ok, I am going to try
OpenCV => 4.6 Operating System / Platform => Windows It was too slow to compute DNN with cpu. So I built and checked all of these cmake options to use the GPU.
In the above command, there is no error with CUDA , but the kernel restart when compiling...