Zj3 SSKJr SSKrSSKrSSKJr SSKJr SSK J r SSK J r SSK Jr SS KJrJrJr SS KJrJrJr \R."\5rSS \\\4S \S \S-S\S\\\44 Sjjr"SS\ 5r"SS\ 5rSS/rg))OptionalN)nn) functional)DetrImageProcessor)DetrImageProcessorPil)center_to_corners_format)PILImageResamplingSizeDict#get_image_size_for_max_height_width) TensorTypeloggingrequires_backends image_sizesizemax_sizemod_sizereturncUupESnUbP[[XE455n[[XE455nX- U-U:aX'-U- n[[ U55nXT:a*Un UbUb[Xd-U- 5n OQ[X-U- 5n O@XE::aXA:Xd XT::aXQ:XaXEpO)Un UbUb[Xe-U- 5n O[X-U- 5n UbXU-- n XU-- n X4$)a_ Computes the output image size given the input image size and the desired output size, while ensuring that both height and width are multiples of `mod_size`. This mirrors the YOLOS-specific behavior used in the torch/fast backends and is required so that all YOLOS image processing backends (PIL, torchvision, fast) produce identical output shapes. N)floatminmaxintround) rrrrheightwidthraw_sizemin_original_sizemax_original_sizeowohs x/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/yolos/modular_yolos.py get_size_with_aspect_ratio_yolosr#s MFH!#vo"67!#vo"67  04 7( B36GGHuX'D ~   H$8X&./BT]U*+B /fn%/emB   H$8X%./BT\F*+B = ! = ! 8Oc ^\rSrSrSS\R S\S\SS\R 4U4SjjjrSS\ S \ \ \ -4S jjr S rS rS rSrU=r$)YolosImageProcessor<imagerresamplez0PILImageResampling | tvF.InterpolationMode | intrc $>UR(a@UR(a/[URSSURUR5nOUR(a@UR (a/[ URSSURUR 5nOJUR(a*UR(aURUR4nO[SUS35e[TU],"U4[USUSS9US.UD6nU$) a Resize the image to the given size. Size can be `min_size` (scalar) or `(height, width)` tuple. If size is an int, smaller edge of the image will be matched to this number. Args: image (`torch.Tensor`): Image to resize. size (`SizeDict`): Size of the image's `(height, width)` dimensions after resizing. Available options are: - `{"height": int, "width": int}`: The image will be resized to the exact size `(height, width)`. Do NOT keep the aspect ratio. - `{"shortest_edge": int, "longest_edge": int}`: The image will be resized to a maximum size respecting the aspect ratio and keeping the shortest edge less or equal to `shortest_edge` and the longest edge less or equal to `longest_edge`. - `{"max_height": int, "max_width": int}`: The image will be resized to the maximum size respecting the aspect ratio and keeping the height less or equal to `max_height` and the width less or equal to `max_width`. resample (`PILImageResampling | tvF.InterpolationMode | int`, *optional*, defaults to `PILImageResampling.BILINEAR`): Resampling filter to use if resizing the image. N\Size must contain 'height' and 'width' keys or 'shortest_edge' and 'longest_edge' keys. Got .rrrrr)) shortest_edge longest_edger#shape max_height max_widthr rr ValueErrorsuperresizer selfr(rr)kwargsnew_size __class__s r"r8YolosImageProcessor.resize=s6   $"3"38 BC8H$J\J\^b^o^opH __:5;;rs;KT__^b^l^lmH [[TZZ TZZ0Hnosnttuv     8A;GRZ ^d  r$ threshold target_sizescURURpTUb#[U5[U5:wa [S5e[R R US5nUSSS24RS5upx[U5n Ub[U[5(aS[R"UV s/sHoSPM sn 5n [R"UV s/sHoSPM sn 5n OURS5up[R"XX/SS9RU R 5n XSS2SSS24-n /n[#XxU 5H1unnnXU:nUX:nUX:nUR%UUUS.5 M3 U$s sn fs sn f) ! Converts the raw output of [`YolosForObjectDetection`] into final bounding boxes in (top_left_x, top_left_y, bottom_right_x, bottom_right_y) format. Only supports PyTorch. Args: outputs ([`YolosObjectDetectionOutput`]): Raw outputs of the model. threshold (`float`, *optional*): Score threshold to keep object detection predictions. target_sizes (`torch.Tensor` or `list[tuple[int, int]]`, *optional*): Tensor of shape `(batch_size, 2)` or list of tuples (`tuple[int, int]`) containing the target size `(height, width)` of each image in the batch. If unset, predictions will not be resized. Returns: `list[Dict]`: A list of dictionaries, each dictionary containing the scores, labels and boxes for an image in the batch as predicted by the model. NTMake sure that you pass in as many target sizes as the batch dimension of the logits.rr.dimscoreslabelsboxes)logits pred_boxeslenr6rrsoftmaxrr isinstancelisttorchTensorunbindstacktodevicezipappendr:outputsr?r@ out_logitsout_bboxprobrHrIrJiimg_himg_w scale_fctresultsslbscorelabelboxs r"post_process_object_detection1YolosImageProcessor.post_process_object_detectionjs}& '~~w/A/AH  #:#l"33 j}}$$Z4c3B3h++B/)2  #,-- L%ALqdL%AB L%ALqdL%AB+2215  U5$@aHKKELLYIaqj11E651GAq!)m$Eam$EAM"C NNeusK L 2 &B%As /FF c[S5eNzHSegmentation post-processing is not implemented for Deformable DETR yet.NotImplementedErrorr:s r""post_process_instance_segmentation6YolosImageProcessor.post_process_instance_segmentation!"lmmr$c[S5eNzQSemantic segmentation post-processing is not implemented for Deformable DETR yet.rmros r""post_process_semantic_segmentation6YolosImageProcessor.post_process_semantic_segmentation!"uvvr$c[S5eNzQPanoptic segmentation post-processing is not implemented for Deformable DETR yet.rmros r""post_process_panoptic_segmentation6YolosImageProcessor.post_process_panoptic_segmentationrwr$Ng?N)__name__ __module__ __qualname____firstlineno__rQrRr rr8rr rPtuplerirprurz__static_attributes__ __classcell__r=s@r"r&r&<s RV +||++MN +  ++\Y]3"'3=G$u+=U3jnwwwr$r&c ^\rSrSrSS\R S\S\SS\R 4U4SjjjrSS\ S \ \ \ -4S jjr S rS rS rSrU=r$)YolosImageProcessorPilr(rr)r rc l>UbUO URnUR(aSUR(aB[URSSURUR=(d UR5nOUR (a@UR (a/[URSSUR UR 5nOJUR(a*UR(aURUR4nO[SUS35e[TU]0"U4[USUSS9US.UD6nU$) a Resize the image to the given size. Size can be `min_size` (scalar) or `(height, width)` tuple. If size is an int, smaller edge of the image will be matched to this number. Args: image (`np.ndarray`): Image to resize. size (`SizeDict`): Size of the image's `(height, width)` dimensions after resizing. Available options are: - `{"height": int, "width": int}`: The image will be resized to the exact size `(height, width)`. Do NOT keep the aspect ratio. - `{"shortest_edge": int, "longest_edge": int}`: The image will be resized to a maximum size respecting the aspect ratio and keeping the shortest edge less or equal to `shortest_edge` and the longest edge less or equal to `longest_edge`. - `{"max_height": int, "max_width": int}`: The image will be resized to the maximum size respecting the aspect ratio and keeping the height less or equal to `max_height` and the width less or equal to `max_width`. resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BILINEAR`): Resampling filter to use if resizing the image. Nr+r,r-rr.r/r0)r)r1r2r#r3r4r5r rrr6r7r8r r9s r"r8YolosImageProcessorPil.resizes 6 (38   $"3"38 BC ""!!7T%7%7H __:5;;rs;KT__^b^l^lmH [[TZZ TZZ0Hnosnttuv   !HQK@     r$r?r@c6[US/5 URURpTUb#[U5[U5:wa [ S5e[ R RUS5nUSSS24RS5upx[U5n Ub[U[5(aS[R"UV s/sHoSPM sn 5n [R"UV s/sHoSPM sn 5n OURS5up[R"XX/SS9R!U R"5n XSS2SSS24-n /n[%XxU 5H1unnnXU:nUX:nUX:nUR'UUUS .5 M3 U$s sn fs sn f) rBrQNrCrD.rr.rErG)rrKrLrMr6rrrNrr rOrPrQrRrSrTrUrVrWrXrYs r"ri4YolosImageProcessorPil.post_process_object_detections& $ *&~~w/A/AH  #:#l"33 j}}$$Z4c3B3h++B/)2  #,-- L%ALqdL%AB L%ALqdL%AB+2215  U5$@aHKKELLYIaqj11E651GAq!)m$Eam$EAM"C NNeusK L 2 &B%As <F%Fc[S5erlrmros r"rp9YolosImageProcessorPil.post_process_instance_segmentationrrr$c[S5ertrmros r"ru9YolosImageProcessorPil.post_process_semantic_segmentationrwr$c[S5eryrmros r"rz9YolosImageProcessorPil.post_process_panoptic_segmentationrwr$r|r}r~)rrrrnpndarrayr rr8rr rPrrirprurzrrrs@r"rrs 48 4zz44/0 4  44nY]4"'4=G$u+=U4lnwwwr$r)N) typingrnumpyrrQrtorchvision.transforms.v2rtvF.transformers.models.detr.image_processing_detrr2transformers.models.detr.image_processing_pil_detrrimage_transformsr image_utilsr r r utilsr rr get_loggerrloggerrrr#r&r__all__r|r$r"rs 7MT8\\;;   H %Z\&c3h&'*&69Dj&SV& 38_&Rjw,jwZtw2twn !": ;r$