cCi.SrSSKJr SSKJrJr SSKrSSKJ r SSK J r J r J r Jr SSKJrJrJrJr SS KJr SS KJr \"5(aSSKr"S S \ 5r"S S\ SS9r"SS\ 5rS/rg)z Processor class for SAMHQ. )deepcopy)OptionalUnionN) ImageInput) ImagesKwargsProcessingKwargsProcessorMixinUnpack) AudioInput BatchEncodingPreTokenizedInput TextInput)is_torch_available) VideoInputc\rSrSr%\\\S'\\\\\S'\\\\ \S'\\\\\\S'\\ \S'Sr g) SamHQImagesKwargs#segmentation_maps input_points input_labels input_boxespoint_pad_valueN) __name__ __module__ __qualname____firstlineno__rr__annotations__listfloatint__static_attributes__re/home/james-whalen/.local/lib/python3.13/site-packages/transformers/models/sam_hq/processing_samhq.pyrr#sW ++4U ,--4S ?++$tDK0122c]"r$rc,\rSrSr%\\S'SSS00rSrg)SamHQProcessorKwargs+ images_kwargsrNr)rrrrrr _defaultsr#rr$r%r'r'+s$$ t Ir$r'F)totalc :^\rSrSrSrS/rSrU4SjrSS\\ S\\ \ \ \ \ \ \ 4S\\S \\S \\S \4 S jjrSS jrSrSS\S\R0S \R04SjjrSSjrSSjr\S5rSrSrSSjr Sr!U=r"$)SamHQProcessor4a Constructs a SAM HQ processor which wraps a SAM image processor and an 2D points & Bounding boxes processor into a single processor. [`SamHQProcessor`] offers all the functionalities of [`SamImageProcessor`]. See the docstring of [`~SamImageProcessor.__call__`] for more information. Args: image_processor (`SamImageProcessor`): An instance of [`SamImageProcessor`]. The image processor is a required input. image_processorSamImageProcessorc>[TU]U5 [US5(d [S5e[URS5(d [S5eURR SUlg)Nr/z,image_processor was not properly initializedsizezimage_processor.size is not set longest_edge)super__init__hasattr ValueErrorr/r2 target_size)selfr/ __class__s r%r5SamHQProcessor.__init__Dsb )t.//KL Lt++V44>? ?//44^Dr$imagestextaudiovideokwargsreturnc UR"[4S00UD6nUSRSS5nUSRSS5nUSRSS5n UR"U40USD6n U Sn [ U S5(aU R 5n UR UUU S 9upxn URU U UUU US RS 5USRS 5S 9n U $)z This method uses [`SamImageProcessor.__call__`] method to prepare image(s) for the model. It also prepares 2D points and bounding boxes for the model if they are provided. tokenizer_init_kwargsr)rNrroriginal_sizesnumpy)rrr common_kwargsreturn_tensorsr)rrrrGr) _merge_kwargsr'popr/r6rE_check_and_preprocess_points_normalize_and_convertget) r9r<r=r>r?r@ output_kwargsrrrencoding_image_processorrDs r%__call__SamHQProcessor.__call__Ms4**  "$  %_599.$O $_599.$O #O488M #'#7#7 $ O,$  22BC >7 + ++113N262S2S%%#3T3 / K $(#>#> $ %%#(9==>NO)/:>>?PQ$?$  ('r$c^TbZURTU5m[U4SjT55(dUbURTXG5umn[R"T5mUb[R"U5nUb&URXRSS9n[R"U5nUbUR USU5US'TbUR TSU5US'UbUR USU5US'U$) zJ Normalize and convert the image processor output to the expected format. c3Z># UH oRTSR:Hv M" g7f)rN)shape).0pointrs r% 8SamHQProcessor._normalize_and_convert..s"V{{l1o&;&;;s(+Tis_bounding_boxrrrr)_normalize_batch_coordinatesall_pad_points_and_labelsnparray _to_tensor)r9rNrDrrrrGrs ` r%rK%SamHQProcessor._normalize_and_converts  #<<\>ZLVVVV+151L1L$l2.L,88L1L  #88L1L  ";;Kim;nK((;/K  "6:ookSTVd6e $] 3  #7;|UVXf7g $^ 4  #7;|UVXf7g $^ 4''r$c [UVs/sHoDRSPM sn5n/n[U5HuptURSU:wa[[R"U[R "XTRS- S45U-/SS9n[R "X'U/5X''UR U5 M UnX4$s snf)zX The method pads the 2D points and labels to the maximum number of points in the batch. r)axis)maxrS enumerater^ concatenatezerosappend)r9rrrrUexpected_nb_pointsprocessed_input_pointsis r%r]%SamHQProcessor._pad_points_and_labelss!l!KlU++a.l!KL!#!,/HA{{1~!33BHH&8;;q>&I1%MNQ``ahi#%))LOo=N"O  " ) )% 0 0. ))"LsCr8coordscUupVURRX1S9upx[U5R[5nU(aUR SSS5nUSX- -US'USXu- -US'U(aUR SS5nU$)zm Expects a numpy array of length 2 in the final dimension. Requires the original image size in (H,W) format. )r3rc).r).rZ)r/_get_preprocess_shaperastyper!reshape) r9r8rn original_sizerYold_hold_wnew_hnew_ws r%_normalize_coordinates%SamHQProcessor._normalize_coordinatess % ++AA-Aj &!((/ ^^B1-F5=9v5=9v ^^B*F r$cUcg[US5(aUR5R5n[U[5nUn[ U5H=nU(aU(d O.U=(a [US[5nU(aUSOSnM? U(d [ U5eUVs/sHn[R"XS9PM sn$s snf)a| Preprocess input by converting torch tensors to numpy arrays and validating structure. Args: inputs: The input to process error_message: Error message if validation fails expected_nesting: Expected nesting level (1 for points/labels, 2 for boxes) dtype: Optional data type for numpy array conversion Returns: Processed input as list of numpy arrays or None NrEr)dtype) r6rEtolist isinstancer ranger7r^r_) r9inputs error_messageexpected_nestingr}validcurrent_items r%_preprocess_input SamHQProcessor._preprocess_inputs > 67 # #\\^**,F64('(A:jT:E$+gajG ) ]+ +9??+???s(C cURUS5nURUS5nURUSS[RS9nXU4$)a Check and preprocesses the 2D points, labels and bounding boxes. It checks if the input is valid and if they are, it converts the coordinates of the points and bounding boxes. If a user passes directly a `torch.Tensor`, it is converted to a `numpy.ndarray` and then to a `list`. z7Input points must be a list of list of floating points.z-Input labels must be a list of list integers.z>Input boxes must be a list of list of list of floating points.rc)rr})rr^float32)r9rrrs r%rJ+SamHQProcessor._check_and_preprocess_pointss\--lrsl"%VV^^'%# #+5E^EP  r$