AssertionError Traceback in google collab

[jaishee]

The code is given below

Give path of source image

source_image_path = '/content/gdrive/MyDrive/yolov7/inference/images/horses.jpg'

with torch.no_grad():
weights, imgsz = opt['weights'], opt['img-size']
set_logging()
device = select_device(opt['device'])
half = device.type != 'cpu'
model = attempt_load(weights, map_location=device) # load FP32 model
stride = int(model.stride.max()) # model stride
imgsz = check_img_size(imgsz, s=stride) # check img_size
if half:
model.half()

names = model.module.names if hasattr(model, 'module') else model.names
colors = [[random.randint(0, 255) for _ in range(3)] for _ in names]
if device.type != 'cpu':
model(torch.zeros(1, 3, imgsz, imgsz).to(device).type_as(next(model.parameters())))

img0 = cv2.imread(source_image_path)
img = letterbox(img0, imgsz, stride=stride)[0]
img = img[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB, to 3x416x416
img = np.ascontiguousarray(img)
img = torch.from_numpy(img).to(device)
img = img.half() if half else img.float() # uint8 to fp16/32
img /= 255.0 # 0 - 255 to 0.0 - 1.0
if img.ndimension() == 3:
img = img.unsqueeze(0)

Inference

t1 = time_synchronized()
pred = model(img, augment= False)[0]

Apply NMS

classes = None
if opt['classes']:
classes = []
for class_name in opt['classes']:

  classes.append(names.index(class_name))

if classes:

classes = [i for i in range(len(names)) if i not in classes]

pred = non_max_suppression(pred, opt['conf-thres'], opt['iou-thres'], classes= [17], agnostic= False)
t2 = time_synchronized()
for i, det in enumerate(pred):
s = ''
s += '%gx%g ' % img.shape[2:] # print string
gn = torch.tensor(img0.shape)[[1, 0, 1, 0]]
if len(det):
det[:, :4] = scale_coords(img.shape[2:], det[:, :4], img0.shape).round()

  for c in det[:, -1].unique():
    n = (det[:, -1] == c).sum()  # detections per class
    s += f"{n} {names[int(c)]}{'s' * (n > 1)}, "  # add to string

  for *xyxy, conf, cls in reversed(det):

    label = f'{names[int(cls)]} {conf:.2f}'
    plot_one_box(xyxy, img0, label=label, color=colors[int(cls)], line_thickness=3)

The errors

AssertionError Traceback (most recent call last)
in <cell line: 5>()
6 weights, imgsz = opt['weights'], opt['img-size']
7 set_logging()
----> 8 device = select_device(opt['device'])
9 half = device.type != 'cpu'
10 model = attempt_load(weights, map_location=device) # load FP32 model

/content/gdrive/MyDrive/yolov7/utils/torch_utils.py in select_device(device, batch_size)
69 elif device: # non-cpu device requested
70 os.environ['CUDA_VISIBLE_DEVICES'] = device # set environment variable
---> 71 assert torch.cuda.is_available(), f'CUDA unavailable, invalid device {device} requested' # check availability
72
73 cuda = not cpu and torch.cuda.is_available()

AssertionError: CUDA unavailable, invalid device 0 requested