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Update main_tensorrt_gpu.py (#27)
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@ -97,6 +97,11 @@ def main():
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im = cp.moveaxis(npImg, 3, 1)
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im = cp.moveaxis(npImg, 3, 1)
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im = torch.from_numpy(cp.asnumpy(im)).to('cuda')
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im = torch.from_numpy(cp.asnumpy(im)).to('cuda')
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#Converting to numpy for visuals
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im0 = im[0].permute(1, 2, 0) * 255
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im0 = im0.cpu().numpy().astype(np.uint8)
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im0 = cv2.cvtColor(im0, cv2.COLOR_RGB2BGR) #Image has to be in BGR for visualization
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# Detecting all the objects
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# Detecting all the objects
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results = model(im)
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results = model(im)
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@ -159,10 +164,10 @@ def main():
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idx = 0
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idx = 0
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# draw the bounding box and label on the frame
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# draw the bounding box and label on the frame
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label = "{}: {:.2f}%".format("Human", confidence * 100)
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label = "{}: {:.2f}%".format("Human", confidence * 100)
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cv2.rectangle(npImg, (startX, startY), (endX, endY),
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cv2.rectangle(im0, (startX, startY), (endX, endY),
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COLORS[idx], 2)
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COLORS[idx], 2)
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y = startY - 15 if startY - 15 > 15 else startY + 15
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y = startY - 15 if startY - 15 > 15 else startY + 15
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cv2.putText(npImg, label, (startX, y),
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cv2.putText(im0, label, (startX, y),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, COLORS[idx], 2)
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, COLORS[idx], 2)
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# Forced garbage cleanup every second
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# Forced garbage cleanup every second
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@ -178,7 +183,7 @@ def main():
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# See visually what the Aimbot sees
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# See visually what the Aimbot sees
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if visuals:
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if visuals:
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cv2.imshow('Live Feed', npImg)
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cv2.imshow('Live Feed', im0)
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if (cv2.waitKey(1) & 0xFF) == ord('q'):
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if (cv2.waitKey(1) & 0xFF) == ord('q'):
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exit()
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exit()
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camera.stop()
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camera.stop()
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