so: Debian 10
cpu: Ryzen 3700x
ram: 32 Gb
gpu: GTX1060 6 Gb

nvidia-smi

Tue Sep 21 00:07:34 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.84 Driver Version: 460.84 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce GTX 106... On | 00000000:08:00.0 Off | N/A |
| 37% 57C P0 24W / 120W | 22MiB / 6077MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 1472 G /usr/lib/xorg/Xorg 15MiB |
| 0 N/A N/A 1785 G /usr/bin/gnome-shell 4MiB |
+-----------------------------------------------------------------------------+

Inference with some images doesn't work.

python3 detect.py --weights yolov5s.pt --conf 0.25 --source /dev/shm/799834/ --project /dev/shm/porcodio/

Unable to init server: Could not connect: Connection refused
Unable to init server: Impossibile connettersi: Connection refused

(detect.py:24881): Gdk-CRITICAL **: 00:05:26.480: gdk_cursor_new_for_display: assertion 'GDK_IS_DISPLAY (display)' failed
Namespace(agnostic_nms=False, augment=False, classes=None, conf_thres=0.25, device='', exist_ok=False, img_size=640, iou_thres=0.45, name='exp', project='/dev/shm/porcodio/', save_conf=False, save_txt=False, source='/dev/shm/799834/', update=False, view_img=False, weights=['yolov5s.pt'])
Using torch 1.7.1 CUDA:0 (GeForce GTX 1060 6GB, 6077MB)

Fusing layers...
Model Summary: 232 layers, 7459581 parameters, 0 gradients, 17.5 GFLOPS
image 1/52 /dev/shm/799834/secondo_10.38.jpg: 384x640 Done. (0.025s)
image 2/52 /dev/shm/799834/secondo_12.38.jpg: 384x640 Done. (0.023s)
image 3/52 /dev/shm/799834/secondo_2.41.jpg: 384x640 Done. (0.026s)
image 4/52 /dev/shm/799834/secondo_2.58.jpg: 384x640 Done. (0.027s)
image 5/52 /dev/shm/799834/secondo_2.69.jpg: 384x640 Done. (0.022s)
image 6/52 /dev/shm/799834/secondo_2.83.jpg: 384x640 Done. (0.021s)
image 7/52 /dev/shm/799834/secondo_22.17.jpg: 384x640 Done. (0.021s)
image 8/52 /dev/shm/799834/secondo_22.29.jpg: 384x640 Done. (0.023s)
image 9/52 /dev/shm/799834/secondo_22.41.jpg: 384x640 Done. (0.022s)
image 10/52 /dev/shm/799834/secondo_22.58.jpg: 384x640 Done. (0.030s)
image 11/52 /dev/shm/799834/secondo_22.7.jpg: 384x640 Done. (0.025s)
image 12/52 /dev/shm/799834/secondo_23.37.jpg: 384x640 Done. (0.027s)
image 13/52 /dev/shm/799834/secondo_23.49.jpg: 384x640 Done. (0.021s)
image 14/52 /dev/shm/799834/secondo_25.03.jpg: 384x640 Done. (0.020s)
image 15/52 /dev/shm/799834/secondo_25.18.jpg: 384x640 Done. (0.021s)
image 16/52 /dev/shm/799834/secondo_25.3.jpg: 384x640 Done. (0.021s)
image 17/52 /dev/shm/799834/secondo_25.42.jpg: 384x640 Done. (0.022s)
image 18/52 /dev/shm/799834/secondo_25.58.jpg: 384x640 Done. (0.022s)
image 19/52 /dev/shm/799834/secondo_25.7.jpg: 384x640 Done. (0.020s)
image 20/52 /dev/shm/799834/secondo_25.82.jpg: 384x640 Done. (0.020s)
image 21/52 /dev/shm/799834/secondo_25.94.jpg: 384x640 Done. (0.021s)
image 22/52 /dev/shm/799834/secondo_26.06.jpg: 384x640 Done. (0.020s)
image 23/52 /dev/shm/799834/secondo_26.18.jpg: 384x640 Done. (0.020s)
image 24/52 /dev/shm/799834/secondo_26.7.jpg: 384x640 Done. (0.021s)
image 25/52 /dev/shm/799834/secondo_26.83.jpg: 384x640 Done. (0.020s)
image 26/52 /dev/shm/799834/secondo_26.98.jpg: 384x640 Done. (0.021s)
image 27/52 /dev/shm/799834/secondo_27.09.jpg: 384x640 Done. (0.020s)
image 28/52 /dev/shm/799834/secondo_27.21.jpg: 384x640 Done. (0.020s)
image 29/52 /dev/shm/799834/secondo_27.37.jpg: 384x640 Done. (0.020s)
image 30/52 /dev/shm/799834/secondo_27.49.jpg: 384x640 1 wild boars, Done. (0.021s)
image 31/52 /dev/shm/799834/secondo_27.62.jpg: 384x640 Done. (0.020s)
image 32/52 /dev/shm/799834/secondo_27.78.jpg: 384x640 Done. (0.020s)
image 33/52 /dev/shm/799834/secondo_27.93.jpg: 384x640 Done. (0.020s)
image 34/52 /dev/shm/799834/secondo_28.05.jpg: 384x640 Done. (0.020s)
image 35/52 /dev/shm/799834/secondo_28.17.jpg: 384x640 Done. (0.020s)
image 36/52 /dev/shm/799834/secondo_28.29.jpg: 384x640 Done. (0.019s)
image 37/52 /dev/shm/799834/secondo_28.41.jpg: 384x640 Done. (0.020s)
image 38/52 /dev/shm/799834/secondo_28.51.jpg: 384x640 Done. (0.020s)
image 39/52 /dev/shm/799834/secondo_3.01.jpg: 384x640 Done. (0.019s)
image 40/52 /dev/shm/799834/secondo_3.13.jpg: 384x640 Done. (0.019s)
image 41/52 /dev/shm/799834/secondo_3.28.jpg: 384x640 Done. (0.019s)
image 42/52 /dev/shm/799834/secondo_3.37.jpg: 384x640 Done. (0.020s)
image 43/52 /dev/shm/799834/secondo_3.54.jpg: Traceback (most recent call last):
File "detect.py", line 182, in
detect()
File "detect.py", line 85, in detect
tmp_pred = pred[0][torch.tensor(x)]
IndexError: tensors used as indices must be long, byte or bool tensors

What AI model do we use,
YoloV5 or is there any other option?

Project Name

Horizon Wildlife Poland

Description

Horizon Wildlife Poland is a system built on the latest technology in communication and artificial intelligence that provides users with a seamless and easy to use experience when reporting sightseeing while delivering state of the art analytics on the backend.

Find datasets, u can look for YoloV5 data sets, but any datasets will work. The more the merrier.

• 1. Anyhogs
• 2. Specific Hogs, Like baby hog, papa hog, etc
• 3. Images with the classification of dead hogs decide