Delete ixc_utils.py~

ixc_utils.py~

@@ -1,136 +0,0 @@
-import torch
-import numpy as np
-import torchvision
-from PIL import Image, ImageDraw, ImageFont
-from torchvision.transforms.functional import InterpolationMode
-import torchvision.transforms as transforms
-from decord import VideoReader
-
-def padding_336(b, pad=336):
-    width, height = b.size
-    tar = int(np.ceil(height / pad) * pad)
-    top_padding = 0 # int((tar - height)/2)
-    bottom_padding = tar - height - top_padding
-    left_padding = 0
-    right_padding = 0
-    b = transforms.functional.pad(b, [left_padding, top_padding, right_padding, bottom_padding], fill=[255,255,255])
-
-    return b
-
-def Image_transform(img, hd_num=25):
-    width, height = img.size
-    trans = False
-    if width < height:
-        img = img.transpose(Image.TRANSPOSE)
-        trans = True
-        width, height = img.size
-    ratio = (width/ height)
-    scale = 1
-    while scale*np.ceil(scale/ratio) <= hd_num:
-        scale += 1
-    scale -= 1
-    scale = min(np.ceil(width / 560), scale)
-    new_w = int(scale * 560)
-    new_h = int(new_w / ratio)
-    #print (scale, f'{height}/{new_h}, {width}/{new_w}')
-
-    img = transforms.functional.resize(img, [new_h, new_w],)
-    img = padding_336(img, 560)
-    width, height = img.size
-    if trans:
-        img = img.transpose(Image.TRANSPOSE)
-
-    return img
-
-
-def Video_transform(img, hd_num=25):
-    width, height = img.size
-    trans = False
-    if width < height:
-        img = img.transpose(Image.TRANSPOSE)
-        trans = True
-        width, height = img.size
-    ratio = (width/ height)
-    scale = 1
-    new_h = int(scale * 560)
-    new_w = int(new_h * ratio)
-    #print (new_h, new_w)
-
-    img = transforms.functional.resize(img, [new_h, new_w],)
-    img = img.transpose(Image.TRANSPOSE)
-    img = padding_336(img, 560)
-    width, height = img.size
-    if not trans:
-        img = img.transpose(Image.TRANSPOSE)
-
-    return img
-
-def frame2img(imgs):
-    new_imgs = []
-    for img in imgs:
-        w, h = img.size
-        scale = w/h
-        if w > h:
-            new_w = 560 * 2
-            new_h = int(560 * 2 / scale)
-        else:
-            new_w = int(560 * 2 * scale)
-            new_h = 560 * 2
-        img = transforms.functional.resize(img, [new_h, new_w],)
-        new_imgs.append(img)
-    imgs = new_imgs
-    new_w = 0
-    new_h = 0
-    pad = 40
-    #font = ImageFont.truetype(os.path.join(config._name_or_path, "SimHei.ttf"), pad)
-    if w > h:
-        for im in imgs:
-            w,h = im.size
-            new_w = max(new_w, w)
-            new_h += h + 10 + pad
-        new_img = Image.new('RGB', (new_w, new_h), 'white')
-        draw = ImageDraw.Draw(new_img)
-        curr_h = 0
-        for idx, im in enumerate(imgs):
-            w,h = im.size
-            new_img.paste(im, (0, pad + curr_h))
-            draw.text((0, curr_h ), f'<IMAGE {idx}>', font=font, fill='black')
-            if idx + 1 < len(imgs):
-                draw.line([(0, pad +curr_h + h +5), (new_w, pad +curr_h + h +5)], fill = 'black', width=2)
-            curr_h += h + 10 + pad
-        #print (new_w, new_h)
-    else:
-        for im in imgs:
-            w,h = im.size
-            new_w += w + 10
-            new_h = max(new_h, h)
-        new_h += pad
-        new_img = Image.new('RGB', (new_w, new_h), 'white')
-        draw = ImageDraw.Draw(new_img)
-        curr_w = 0
-        for idx, im in enumerate(imgs):
-            w,h = im.size
-            new_img.paste(im, (curr_w, pad))
-            draw.text((curr_w, 0), f'<IMAGE {idx}>', font=font, fill='black')
-            if idx + 1 < len(imgs):
-                draw.line([(curr_w + w + 5, 0), (curr_w + w + 5, new_h)], fill = 'black', width=2)
-            curr_w += w + 10
-    return new_img
-
-def load_video(video_path, num_frm=32, start=None, end=None):
-    vid = VideoReader(video_path, num_threads=1)
-    fps = vid.get_avg_fps()
-    t_stride = int(round(float(fps) / int(1)))
-    start_idx = 0 if start is None else start
-    end_idx = len(vid) if end is None else end
-    all_pos = list(range(start_idx, end_idx, t_stride))
-    images = [vid[i].numpy() for i in all_pos]
-    if len(images) > num_frm:
-        num_frm = min(num_frm, len(images))
-        step_size = len(images) / (num_frm + 1)
-        indices = [int(i*step_size) for i in range(num_frm)]
-        images = [images[i] for i in indices]
-    images = [Image.fromarray(arr) for arr in images]
-    image = frame2img(images)
-    return image
-