download small size image
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@ -96,7 +96,13 @@ export default function Editor(props: EditorProps) {
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context.clearRect(0, 0, context.canvas.width, context.canvas.height)
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context.clearRect(0, 0, context.canvas.width, context.canvas.height)
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const currRender = renders[renders.length - 1]
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const currRender = renders[renders.length - 1]
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if (currRender?.src) {
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if (currRender?.src) {
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context.drawImage(currRender, 0, 0)
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context.drawImage(
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currRender,
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0,
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0,
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original.naturalWidth,
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original.naturalHeight
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)
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} else {
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} else {
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context.drawImage(original, 0, 0)
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context.drawImage(original, 0, 0)
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}
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}
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21
main.py
21
main.py
@ -14,9 +14,14 @@ import torch
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from flask import Flask, request, send_file
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from flask import Flask, request, send_file
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from flask_cors import CORS
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from flask_cors import CORS
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from lama_cleaner.helper import (download_model, load_img, norm_img,
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from lama_cleaner.helper import (
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numpy_to_bytes, pad_img_to_modulo,
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download_model,
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resize_max_size)
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load_img,
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norm_img,
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numpy_to_bytes,
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pad_img_to_modulo,
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resize_max_size,
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)
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NUM_THREADS = str(multiprocessing.cpu_count())
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NUM_THREADS = str(multiprocessing.cpu_count())
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@ -63,11 +68,11 @@ def process():
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res_np_img = run(image, mask)
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res_np_img = run(image, mask)
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# resize to original size
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# resize to original size
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res_np_img = cv2.resize(
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# res_np_img = cv2.resize(
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res_np_img,
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# res_np_img,
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dsize=(original_shape[1], original_shape[0]),
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# dsize=(original_shape[1], original_shape[0]),
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interpolation=interpolation,
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# interpolation=interpolation,
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)
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# )
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return send_file(
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return send_file(
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io.BytesIO(numpy_to_bytes(res_np_img)),
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io.BytesIO(numpy_to_bytes(res_np_img)),
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