j |ddlmZddlZddlZddlmZddlmZ ddl m Z ddl m Z mZgdZdd ejd ed ejfd Z dd ejdejdeded eejejff dZd ejdejdeeeeefd eejejffdZd ejdeeefd ejfdZdS))deepcopyN)gaussian_filter) functional)rotate_abs_geoms)create_shadow_mask crop_boxes) invert_colors rotate_samplecrop_detection random_shadow333333?imgmin_valreturnctj|d}|jdkr|jddddgngd}|d|z t j|zz}|jtjkr=||j|ztj}n|||jz}|jtjkrd|z nd|z }|S) zInvert the colors of an image Args: img : torch.Tensor, the image to invert min_val : minimum value of the random shift Returns: the inverted image )num_output_channelsrr)rrr)dtype) Frgb_to_grayscalendimshapetorchrandruint8to)rrout shift_shape rgb_shifts f/var/www/html/Carbon-Document/venv/lib/python3.11/site-packages/doctr/transforms/functional/pytorch.pyr r s Sa 8 8 8C-0X]]39Q<Aq)) K1w;%*[*A*AAAI yEKvvIOv,,y8<<5;<OOILLsyL111yEK//#))QWC JFgeomsangleexpandcVtj||d|}|dd}t|}|jdddkr[t j|dkrB|ddddgfxx|jdzcc<|ddddgfxx|jd zcc<nq|jddd krOt j|dkr6|d xx|jdzcc<|d xx|jd zcc<nt d t|||jdd|tj }|d |jdz |d <|d |jdz |d <|t j t j |dddfS)aRotate image around the center, interpolation=NEAREST, pad with 0 (black) Args: img: image to rotate geoms: array of geometries of shape (N, 4) or (N, 4, 2) angle: angle in degrees. +: counter-clockwise, -: clockwise expand: whether the image should be padded before the rotation Returns: A tuple of rotated img (tensor), rotated geometries of shape (N, 4, 2) r)r&fillr'Nrr)r)rr*).r).rzinvalid format for arg `geoms`)decimals) rrotaterrnpmaxAssertionErrorrastypefloat32cliparound)rr%r&r' rotated_img_geoms rotated_geomss r#r r ,s"(3e!FCCCKbqb/K e__F |ABB4 6&>>Q   111q!f9   2 .    111q!f9   2 .    abb V # # 6&>>Q   6NNNcim +NNN 6NNNcim +NNN=>>>!1  !""  !!  fRZ *&1K4Ea4HHM&)&1K4Ea4HHM&  -" E E Eq!LL LLr$boxescrop_boxcVtd|Drtd|jdd\}}tt |d|dz ztt |d|dz z}}tt |d|dz ztt |d|dz z}}t j|||||z ||z } t||dkr|n||||f}| |fS) aKCrop and image and associated bboxes Args: img: image to crop boxes: array of boxes to clip, absolute (int) or relative (float) crop_box: box (xmin, ymin, xmax, ymax) to crop the image. Relative coords. Returns: A tuple of cropped image, cropped boxes, where the image is not resized. c3.K|]}|dkp|dkVdS)rrN).0vals r# z!crop_detection..hs/ 2 2#37 cAg 2 2 2 2 2 2r$z0coordinates of arg `crop_box` should be relativer,Nrrr*r) anyr2rintroundrcropr r1) rr:r;hwxminyminxmaxymax cropped_imgs r#r r [s' 2 2 2 2 222QOPPP 9RSS>DAqU8A;!a%01122ChqkQQRU>S8T8T4U4U$DU8A;!a%01122ChqkQQRU>S8T8T4U4U$D&dD$+td{CCK u%))++*:*:hhtTSW@X Y YE  r$ opacity_rangec t|jddfi|}tjj|}tjdd}t ||}dt j|z }| |j  d}||z|zd|z |zzS)atApply a random shadow effect to an image using NumPy for blurring. Args: img: Image to modify (C, H, W) as a PyTorch tensor. opacity_range: The minimum and maximum desired opacity of the shadow. **kwargs: Additional arguments to pass to `create_shadow_mask`. Returns: Shadowed image as a PyTorch tensor (same shape as input). rNg?g@)sigmar) rrr0randomuniformrr from_numpyfloatrdevice unsqueeze)rrMkwargs shadow_maskopacityrO blurred_mask shadow_tensors r#r r ts%SYqrr]==f==Ki/G I  c3 ' 'E";e<<>>M!$$SZ00::1==M ] "S (AK3+> >>r$)r)F)copyrnumpyr0r scipy.ndimagertorchvision.transformsrrdoctr.utils.geometryrbaserr __all__TensorrSr ndarraybooltupler r r r>r$r#rfs  ))))))22222211111100000000 O O Ou|eel8 ,M,M ,M :,M ,M  ,M  5< #$ ,M,M,M,M^  j49%u:T4U 5< #$2?u|?E%,4G?V[Vb??????r$