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Update app.py
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app.py
CHANGED
@@ -13,6 +13,9 @@ import gradio as gr
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from huggingface_hub import snapshot_download
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from PIL import PngImagePlugin
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LARGE_ENOUGH_NUMBER = 100
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PngImagePlugin.MAX_TEXT_CHUNK = LARGE_ENOUGH_NUMBER * (1024**2)
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@@ -28,6 +31,16 @@ def resize(width,img):
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hsize = int((float(img.size[1])*float(wpercent)))
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img = img.resize((basewidth,hsize), Image.ANTIALIAS)
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return img
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def predict(frame1, frame2, times_to_interpolate):
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@@ -37,8 +50,8 @@ def predict(frame1, frame2, times_to_interpolate):
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frame1.save("test1.png")
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frame2.save("test2.png")
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input_frames = ["test1.png", "
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frames = list(
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util.interpolate_recursively_from_files(
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from huggingface_hub import snapshot_download
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from PIL import PngImagePlugin
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from image_tools.sizes import resize_and_crop
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LARGE_ENOUGH_NUMBER = 100
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PngImagePlugin.MAX_TEXT_CHUNK = LARGE_ENOUGH_NUMBER * (1024**2)
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hsize = int((float(img.size[1])*float(wpercent)))
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img = img.resize((basewidth,hsize), Image.ANTIALIAS)
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return img
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def resize_img(img1,img2):
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img_target_size = Image.open(img1)
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img_to_resize = resize_and_crop(
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img2,
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(img_origin_size.size[0],img_origin_size.size[1]), #set width and height to match img1
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crop_origin="middle"
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)
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img_to_resize.save('resized_img2.png')
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def predict(frame1, frame2, times_to_interpolate):
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frame1.save("test1.png")
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frame2.save("test2.png")
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resize_img("test1.png","test2.png")
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input_frames = ["test1.png", "resized_img2.png"]
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frames = list(
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util.interpolate_recursively_from_files(
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