o پi#@sdZ ddlmmZddlZdZdZejj      dd d Z d d Z d dZ ddZ ddZedfddZedfddZddedfddZGdddZdS)z Tensorflow Preprocessing Adapter Allows use of Tensorflow preprocessing pipeline in PyTorch Transform Copyright of original Tensorflow code below. Hacked together by / Copyright 2020 Ross Wightman N 皙??gHzG?g??dc Cst|d||gDtj|}tjj||||||dd}|\} } } t| \} } } t| \}}} t| | ||g}tjj||dd}|WdS1sPwYdS)aGenerates cropped_image using one of the bboxes randomly distorted. See `tf.image.sample_distorted_bounding_box` for more documentation. Args: image_bytes: `Tensor` of binary image data. bbox: `Tensor` of bounding boxes arranged `[1, num_boxes, coords]` where each coordinate is [0, 1) and the coordinates are arranged as `[ymin, xmin, ymax, xmax]`. If num_boxes is 0 then use the whole image. min_object_covered: An optional `float`. Defaults to `0.1`. The cropped area of the image must contain at least this fraction of any bounding box supplied. aspect_ratio_range: An optional list of `float`s. The cropped area of the image must have an aspect ratio = width / height within this range. area_range: An optional list of `float`s. The cropped area of the image must contain a fraction of the supplied image within in this range. max_attempts: An optional `int`. Number of attempts at generating a cropped region of the image of the specified constraints. After `max_attempts` failures, return the entire image. scope: Optional `str` for name scope. Returns: cropped image `Tensor` distorted_bounding_box_cropT)bounding_boxesmin_object_coveredaspect_ratio_range area_range max_attemptsuse_image_if_no_bounding_boxeschannelsN)tf name_scopeimageextract_jpeg_shapesample_distorted_bounding_boxunstackstackdecode_and_crop_jpeg) image_bytesbboxr r rrscopeshaper bbox_begin bbox_size_offset_yoffset_x target_height target_width crop_windowrr(N/home/ubuntu/.local/lib/python3.10/site-packages/timm/data/tf_preprocessing.pyr !s$  $r cCs,t||}t|tj}tt||S)z0At least `x` of `a` and `b` `Tensors` are equal.)requalcastint32 greater_equal reduce_sum)abxmatchr(r(r)_at_least_x_are_equalUs r3c svtjgdtjgdd}t|dddddd tj}t|td }t|fd d fd d S)z!Make a random crop of image_size.)r4rr)r5)dtyperr)rgUUUUUU?)g{Gz?r N)r r rrrrcs tS)N)_decode_and_center_cropr()r image_sizer(r)ls z)_decode_and_random_crop..cstjggdSNr)rrresizer()rr: resize_methodr(r)r;ms) rconstantfloat32r rrr3rcond)rr:r>roriginal_shapebadr()rrr:r>r)_decode_and_random_crop\s$  rDc Cstj|}|d}|d}t||ttt||tjtj}||dd}||dd}t||||g} tjj || dd} tj | g||g|d} | S)z=Crops to center of image with padding then scales image_size.rr5rr) rrrr+ CROP_PADDINGminimumr@r,rrr=) rr:r>r image_height image_widthpadded_center_crop_size offset_height offset_widthr'rr(r(r)r9rs"  r9cCstj|}|S)zRandom horizontal image flip.)rrrandom_flip_left_right)rr(r(r)_flips rNbicubiccCsb|dkr tjjjntjjj}t|||}t|}t|||dg}tjj||r*tj ntj d}|SaAPreprocesses the given image for evaluation. Args: image_bytes: `Tensor` representing an image binary of arbitrary size. use_bfloat16: `bool` for whether to use bfloat16. image_size: image size. interpolation: image interpolation method Returns: A preprocessed image `Tensor`. rOr)r7) rr ResizeMethodBICUBICBILINEARrDrNreshapeconvert_image_dtypebfloat16r@r use_bfloat16r: interpolationr>rr(r(r)preprocess_for_trains rZcCsZ|dkr tjjjntjjj}t|||}t|||dg}tjj||r&tjntj d}|SrP) rrrQrRrSr9rTrUrVr@rWr(r(r)preprocess_for_evals r[FcCs |r t||||St||||S)aPreprocesses the given image. Args: image_bytes: `Tensor` representing an image binary of arbitrary size. is_training: `bool` for whether the preprocessing is for training. use_bfloat16: `bool` for whether to use bfloat16. image_size: image size. interpolation: image interpolation method Returns: A preprocessed image `Tensor` with value range of [0, 255]. )rZr[)r is_trainingrXr:rYr(r(r)preprocess_imagesr]c@s&eZdZd ddZddZdd Zd S) TfPreprocessTransformFrrOcCs>||_t|tr |dn||_||_d|_||_d|_dSr<) r\ isinstancetuplesizerY _image_bytes_build_tf_graph process_imagesess)selfr\rarYr(r(r)__init__s   zTfPreprocessTransform.__init__cCsZtdtjgtjd|_t|j|jd|j|j}Wd|S1s&wY|S)Nz/cpu:0)rr7F) rdevice placeholderstringrbr]r\rarY)rfimgr(r(r)rcs  z%TfPreprocessTransform._build_tf_graphcCsl|jdur t|_|jj|j|j|id}|ddt j }|j dkr.t j |dd}t |d}|S)N) feed_dictrr)axisrE)rerSessionrunrdrbroundclipastypenpuint8ndim expand_dimsrollaxis)rfrrkr(r(r)__call__s    zTfPreprocessTransform.__call__N)FrrO)__name__ __module__ __qualname__rgrcrzr(r(r(r)r^s  r^)rrrr N)__doc__tensorflow.compat.v1compatv1rnumpyru IMAGE_SIZErFdisable_eager_executionr r3rDr9rNrZr[r]r^r(r(r(r)s2  4