New sample code (visible from the above link, too):
from roboflowoak import RoboflowOak
import cv2
import time
import numpy as np
if __name__ == '__main__':
# instantiating an object (rf) with the RoboflowOak module
# API Key: https://docs.roboflow.com/rest-api#obtaining-your-api-key
rf = RoboflowOak(model="YOUR-MODEL-ID", confidence=0.05, overlap=0.5,
version="YOUR-MODEL-VERSION-#", api_key="YOUR-PRIVATE_API_KEY", rgb=True,
depth=True, device=None, blocking=True)
# Running our model and displaying the video output with detections
while True:
t0 = time.time()
# The rf.detect() function runs the model inference
result, frame, raw_frame, depth = rf.detect()
predictions = result["predictions"]
#{
# predictions:
# [ {
# x: (middle),
# y:(middle),
# width:
# height:
# depth: ###->
# confidence:
# class:
# mask: {
# ]
#}
#frame - frame after preprocs, with predictions
#raw_frame - original frame from your OAK
#depth - depth map for raw_frame, center-rectified to the center camera
# timing: for benchmarking purposes
t = time.time()-t0
print("FPS ", 1/t)
print("PREDICTIONS ", [p.json() for p in predictions])
# setting parameters for depth calculation
max_depth = np.amax(depth)
cv2.imshow("depth", depth/max_depth)
# displaying the video feed as successive frames
cv2.imshow("frame", frame)
# how to close the OAK inference window / stop inference: CTRL+q or CTRL+c
if cv2.waitKey(1) == ord('q'):
break
Unfortunately I copied your new code and finding new errors:
Traceback (most recent call last):
File “main.py”, line 17, in
result, frame, raw_frame, depth = rf.detect()
File “…\lib\site-packages\roboflowoak_init_.py”, line 63, in detect
ret = self.dai_pipe.get()
File “…\lib\site-packages\roboflowoak\pipe.py”, line 188, in get
detections = self.detection_depth(detections, depth)
File “…\lib\site-packages\roboflowoak\pipe.py”, line 145, in detection_depth
depth_map = self.disparity_to_depth(depth)
File “…\lib\site-packages\roboflowoak\pipe.py”, line 134, in disparity_to_depth
if disparity == 0:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
Can you please suggest anything? Thanks in advance
@Cecilio what project type are you attempting to deploy to the OAK? Can you confirm it is object detection?
And have you updated to the latest version of the package?
pip install -U roboflowoak
Additionally, can you provide a copy of the code you’re running here (with the API key removed, and you can omit the model id too if you’d like to leave it off the forum)?
Yes, it is object detection project and I have installed the lastest roboflowak package.
Please see below the code:
from roboflowoak import RoboflowOak
import cv2
import time
import numpy as np
if name == ‘main’:
# instantiating an object (rf) with the RoboflowOak module
# API Key: REST API - Roboflow
rf = RoboflowOak(model=“pears-tvvfl”, confidence=0.05, overlap=0.5,
version=“1”, api_key=“”, rgb=True,
depth=True, device=None, blocking=True)
# Running our model and displaying the video output with detections
while True:
t0 = time.time()
# The rf.detect() function runs the model inference
result, frame, raw_frame, depth = rf.detect()
predictions = result[“predictions”]
# {
# predictions:
# [ {
# x: (middle),
# y:(middle),
# width:
# height:
# depth: ###->
# confidence:
# class:
# mask: {
# ]
# }
# frame - frame after preprocs, with predictions
# raw_frame - original frame from your OAK
# depth - depth map for raw_frame, center-rectified to the center camera
# timing: for benchmarking purposes
t = time.time() - t0
print("FPS ", 1 / t)
print("PREDICTIONS ", [p.json() for p in predictions])
# setting parameters for depth calculation
max_depth = np.amax(depth)
cv2.imshow("depth", depth / max_depth)
# displaying the video feed as successive frames
cv2.imshow("frame", frame)
# how to close the OAK inference window / stop inference: CTRL+q or CTRL+c
if cv2.waitKey(1) == ord('q'):
break
I kept trying but having the same error. Could it be possible that the new code introduced a bug as I am not able to execute the script? Thanks in advance
Same problem here !
I’m also trying to deploy an object detection model to an OAK PoE and I have the same error message after removing the visualize argument
For the OAK PoE device, can you try instantiating the “rf” object with depth=False? You are using the SDK with depth enabled on devices that don’t support depth detection.
Additionally, for the OAK-D devices, and general OAK deployment, we have since updated the documentation. You will want to install the package with pip install roboflowoak==0.0.5 for those that have not yet installed the package. For those that have, use pip install -lv roboflowoak==0.0.5
from roboflowoak import RoboflowOak
import cv2
import time
import numpy as np
if __name__ == '__main__':
# instantiating an object (rf) with the RoboflowOak module
# API Key: https://docs.roboflow.com/rest-api#obtaining-your-api-key
rf = RoboflowOak(model="face-detection-mik1i", confidence=0.05, overlap=0.5,
version="15", api_key="XXXXXXXX", rgb=True,
depth=True, device=None, blocking=True)
# Running our model and displaying the video output with detections
while True:
t0 = time.time()
# The rf.detect() function runs the model inference
result, frame, raw_frame, depth = rf.detect()
predictions = result["predictions"]
#{
# predictions:
# [ {
# x: (middle),
# y:(middle),
# width:
# height:
# depth: ###->
# confidence:
# class:
# mask: {
# ]
#}
#frame - frame after preprocs, with predictions
#raw_frame - original frame from your OAK
#depth - depth map for raw_frame, center-rectified to the center camera
# timing: for benchmarking purposes
t = time.time()-t0
print("FPS ", 1/t)
print("PREDICTIONS ", [p.json() for p in predictions])
# setting parameters for depth calculation
# comment out the following 2 lines out if you're using an OAK without Depth
max_depth = np.amax(depth)
cv2.imshow("depth", depth/max_depth)
# displaying the video feed as successive frames
cv2.imshow("frame", frame)
# how to close the OAK inference window / stop inference: CTRL+q or CTRL+c
if cv2.waitKey(1) == ord('q'):
break
Note that the “3 lines” referenced for deletion no longer exist in install_requirements.py (I just ran the process today), but the “48 lines” to delete do still exist. After deleting the 48 lines, be sure to “Write Out” (CTRL + O) and then save the changes.
