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Update centerface.py #108

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Update centerface.py #108

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13 changes: 6 additions & 7 deletions prj-tensorrt/centerface.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,9 @@ def __init__(self, landmarks=True):
runtime = trt.Runtime(self.trt_logger)
self.net = runtime.deserialize_cuda_engine(f.read())
self.img_h_new, self.img_w_new, self.scale_h, self.scale_w = 0, 0, 0, 0
self.engine = self.net
# Create the context for this engine
self.context = self.engine.create_execution_context()

def __call__(self, img, height, width, threshold=0.5):
h, w = img.shape[:2]
Expand Down Expand Up @@ -67,12 +70,8 @@ def do_inference(context, bindings, inputs, outputs, stream, batch_size=1):

image_cv = cv2.resize(img, dsize=(self.img_w_new, self.img_h_new))
blob = np.expand_dims(image_cv[:, :, (2, 1, 0)].transpose(2, 0, 1), axis=0).astype("float32")
engine = self.net

# Create the context for this engine
context = engine.create_execution_context()
# Allocate buffers for input and output
inputs, outputs, bindings, stream = allocate_buffers(engine) # input, output: host # bindings

inputs, outputs, bindings, stream = allocate_buffers(self.engine) # input, output: host # bindings

# Do inference
shape_of_output = [(1, 1, int(self.img_h_new / 4), int(self.img_w_new / 4)),
Expand All @@ -82,7 +81,7 @@ def do_inference(context, bindings, inputs, outputs, stream, batch_size=1):
# Load data to the buffer
inputs[0].host = blob.reshape(-1)
begin = datetime.datetime.now()
trt_outputs = do_inference(context, bindings=bindings, inputs=inputs, outputs=outputs, stream=stream) # numpy data
trt_outputs = do_inference(self.context, bindings=bindings, inputs=inputs, outputs=outputs, stream=stream) # numpy data
end = datetime.datetime.now()
print("gpu times = ", end - begin)

Expand Down