def __getitem__()

in data/dryice1.py [0:0]

• 52 lines of code
• 13 McCabe index (conditional complexity)

    def __getitem__(self, idx):
        frame, cam = self.framecamlist[idx]

        result = {}

        validinput = True

        # fixed camera images
        if "fixedcamimage" in self.keyfilter:
            ninput = len(self.fixedcameras)

            fixedcamimage = np.zeros((3 * ninput, 512, 334), dtype=np.float32)
            for i in range(ninput):
                imagepath = (
                        "experiments/dryice1/data/cam{}/image{:04}.jpg"
                        .format(self.fixedcameras[i], int(frame)))
                image = np.asarray(Image.open(imagepath), dtype=np.uint8)[::2, ::2, :].transpose((2, 0, 1)).astype(np.float32)
                if np.sum(image) == 0:
                    validinput = False
                fixedcamimage[i*3:(i+1)*3, :, :] = image
            fixedcamimage[:] -= self.imagemean
            fixedcamimage[:] /= self.imagestd
            result["fixedcamimage"] = fixedcamimage

        result["validinput"] = np.float32(1.0 if validinput else 0.0)

        # image data
        if cam is not None:
            if "camera" in self.keyfilter:
                # camera data
                result["camrot"] = np.dot(self.transf[:3, :3].T, self.camrot[cam].T).T
                result["campos"] = np.dot(self.transf[:3, :3].T, self.campos[cam] - self.transf[:3, 3])
                result["focal"] = self.focal[cam]
                result["princpt"] = self.princpt[cam]
                result["camindex"] = self.allcameras.index(cam)

            if "image" in self.keyfilter:
                # image
                imagepath = (
                        "experiments/dryice1/data/cam{}/image{:04}.jpg"
                        .format(cam, int(frame)))
                image = np.asarray(Image.open(imagepath), dtype=np.uint8).transpose((2, 0, 1)).astype(np.float32)
                height, width = image.shape[1:3]
                valid = np.float32(1.0) if np.sum(image) != 0 else np.float32(0.)
                result["image"] = image
                result["imagevalid"] = valid

            if "pixelcoords" in self.keyfilter:
                if self.subsampletype == "patch":
                    indx = np.random.randint(0, width - self.subsamplesize + 1)
                    indy = np.random.randint(0, height - self.subsamplesize + 1)

                    px, py = np.meshgrid(
                            np.arange(indx, indx + self.subsamplesize).astype(np.float32),
                            np.arange(indy, indy + self.subsamplesize).astype(np.float32))
                elif self.subsampletype == "random":
                    px = np.random.randint(0, width, size=(self.subsamplesize, self.subsamplesize)).astype(np.float32)
                    py = np.random.randint(0, height, size=(self.subsamplesize, self.subsamplesize)).astype(np.float32)
                elif self.subsampletype == "random2":
                    px = np.random.uniform(0, width - 1e-5, size=(self.subsamplesize, self.subsamplesize)).astype(np.float32)
                    py = np.random.uniform(0, height - 1e-5, size=(self.subsamplesize, self.subsamplesize)).astype(np.float32)
                else:
                    px, py = np.meshgrid(np.arange(width).astype(np.float32), np.arange(height).astype(np.float32))

                result["pixelcoords"] = np.stack((px, py), axis=-1)

        return result