Inference pipeline

[abhigoku10]

@Yejin0111 hi thanks for sharing the code base i had few queiers

1. There is no test / inference .py file to test on the image / video? can u provide it or should we write it ourself
2. THe output of the model is a tensor for a given image is like this
   "len(outputs[0])
   80
   outputs
   tensor([[-283.4771, 100.7004, -25.2342, -31.9534, 137.3260, -100.9781,\n 42.4637, 287.5411, -41.0544, 32.0411, -62.8640, -84.3158,\n 27.4881, -95.6437, -16.3595, 284.4416, 90.6528, 18.8440,\n 145.0567, -112.4063, -55.4868, -88.7339, -18.2153, 41.3703,\n -2.9013, -51.1030, -53.5617, 11.8468, -112.8955, 77.1685,\n 52.6853, 19.6216, -109.0874, -43.6641, -102.1985, 37.9849,\n 172.5355, -3.5291, -218.5259, 155.2649, -61.3687, 13.4691,\n 102.0848, 151.9249, 32.8274, -30.5526, -159.6230, 169.1592,\n 136.3983, -139.8331, -97.2136, -105.8271, 97.7561, -17.9792,\n -11.9392, -105.7749, -169.9196, 119.8365, 47.2773, 79.9587,\n -38.9244, -117.4937, -27.4478, -82.6502, -29.5093, -16.8091,\n 52.4464, -77.0061, 30.4399, 120.5782, 45.0289, -178.4777,\n -94.0661, 270.4139, 125.4486, -76.9411, -5.2130, -25.1496,\n -75.8140, -230.2440]], device='cuda:0')"
   How to obtain the output class for this image ?
3. how can i visualize the intermediate layers as shown in paper
   THanks in advance

[THUeeY]

Me too, I meet the same problem. Maybe we need to use torch.Sigmoid(outputs).