0db94786a7a463fed49825811fac903f1f1fc3c8,python/caffe/detector.py,Detector,detect_windows,#Detector#,58

Before Change

                window_inputs.append(self.crop(image, window))

        // Run through the net (warping windows to input dimensions).
        caffe_in = np.asarray([self.preprocess(self.inputs[0], window_in)
                    for window_in in window_inputs])
        out = self.forward_all(**{self.inputs[0]: caffe_in})
        predictions = out[self.outputs[0]].squeeze(axis=(2,3))

        // Package predictions with images and windows.

After Change

                window_inputs.append(self.crop(image, window))

        // Run through the net (warping windows to input dimensions).
        caffe_in = np.zeros((len(window_inputs), window_inputs[0].shape[2])
                            + self.blobs[self.inputs[0]].data.shape[2:],
                            dtype=np.float32)
        for ix, window_in in enumerate(window_inputs):
            caffe_in[ix] = self.preprocess(self.inputs[0], window_in)
        out = self.forward_all(**{self.inputs[0]: caffe_in})
        predictions = out[self.outputs[0]].squeeze(axis=(2,3))

Instances