{"record":{"id":"22579220cdd19a12","repo":"keras-team/keras","slug":"invalid-channel-size-expected-3-rgb-or-1-grays-225792","errorCode":null,"errorMessage":"Invalid channel size: expected 3 (RGB) or 1 (Grayscale). Received input with shape: images.shape={tuple(images_shape)}","messagePattern":"Invalid channel size: expected 3 \\(RGB\\) or 1 \\(Grayscale\\)\\. Received input with shape: images\\.shape=(.+?)","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"keras/src/ops/image.py","lineNumber":31,"sourceCode":"        self.data_format = backend.standardize_data_format(data_format)\n\n    def call(self, images):\n        return backend.image.rgb_to_grayscale(\n            images, data_format=self.data_format\n        )\n\n    def compute_output_spec(self, images):\n        images_shape = list(images.shape)\n        if len(images_shape) not in (3, 4):\n            raise ValueError(\n                \"Invalid images rank: expected rank 3 (single image) \"\n                \"or rank 4 (batch of images). \"\n                f\"Received: images.shape={images_shape}\"\n            )\n        channels_axis = -1 if self.data_format == \"channels_last\" else -3\n        channels = images_shape[channels_axis]\n        if channels is not None and channels not in (1, 3):\n            raise ValueError(\n                \"Invalid channel size: expected 3 (RGB) or 1 (Grayscale). \"\n                f\"Received input with shape: images.shape={tuple(images_shape)}\"\n            )\n        images_shape[channels_axis] = 1\n        return KerasTensor(shape=images_shape, dtype=images.dtype)\n\n\n@keras_export(\"keras.ops.image.rgb_to_grayscale\")\ndef rgb_to_grayscale(images, data_format=None):\n    \"\"\"Convert RGB images to grayscale.\n\n    This function converts RGB images to grayscale images. It supports both\n    3D and 4D tensors.\n\n    Args:\n        images: Input image or batch of images. Must be 3D or 4D.\n        data_format: A string specifying the data format of the input tensor.\n            It can be either `\"channels_last\"` or `\"channels_first\"`.","sourceCodeStart":13,"sourceCodeEnd":49,"githubUrl":"https://github.com/keras-team/keras/blob/7a34a03db60bf60042242d6a556fc3be119046a5/keras/src/ops/image.py#L13-L49","documentation":"After the rank check, this image op reads the channels axis (last for channels_last, third-from-last for channels_first) and requires exactly 1 (grayscale) or 3 (RGB). Any other channel count (2, 4, 255, None excluded) raises this ValueError because the op only defines grayscale/RGB semantics.","triggerScenarios":"Passing RGBA images (channels=4), palette images, or tensors whose channel axis holds something else (e.g. classes); reading PNGs with alpha via PIL without convert().","commonSituations":"Loading RGBA PNGs or palette-mode images with PIL and feeding the raw array; data saved as (H,W,4); accidentally putting time or class axis in the channel position.","solutions":["Convert images before the op: Image.open(p).convert('RGB') or convert('L') for grayscale","Slice off extra channels: images = images[..., :3] for RGBA","If the extra axis is not channels, move it out of the channel position or fix data_format"],"exampleFix":"# before\nimg = np.array(Image.open(p))  # RGBA (H,W,4)\ny = op(img)  # ValueError\n\n# after\nimg = np.array(Image.open(p).convert('RGB'))  # (H,W,3)\ny = op(img)","handlingStrategy":"validation","validationCode":"c = images.shape[-1 if data_format == 'channels_last' else -3]\nassert c in (1, 3), f'bad channels: {c}'","typeGuard":"def has_valid_channels(images, data_format='channels_last') -> bool:\n    c = images.shape[-1 if data_format == 'channels_last' else -3]\n    return c is None or c in (1, 3)","tryCatchPattern":null,"preventionTips":["Always open images with convert('RGB') or convert('L')","Drop alpha channels at load time: arr[..., :3]"],"tags":["keras","image","channel-validation","shape-mismatch"],"backgroundTag":"image-channel-validation","analyzedSha":"7a34a03db60bf60042242d6a556fc3be119046a5","analyzedAt":"2026-08-25T21:25:25.994Z","schemaVersion":2},"datasetVersion":"2026-08-26T02:17:13.382Z"}