From e06af50389f849be0bfe4fa97d39f4519ef2c711 Mon Sep 17 00:00:00 2001
From: adamhrv <adam@ahprojects.com>
Date: Fri, 18 Jan 2019 11:00:18 +0100
Subject: change to cli_proc

---
 megapixels/commands/processor/resize_dataset.py | 149 ++++++++++++++++++++++++
 1 file changed, 149 insertions(+)
 create mode 100644 megapixels/commands/processor/resize_dataset.py

(limited to 'megapixels/commands/processor/resize_dataset.py')

diff --git a/megapixels/commands/processor/resize_dataset.py b/megapixels/commands/processor/resize_dataset.py
new file mode 100644
index 00000000..3a6ec15f
--- /dev/null
+++ b/megapixels/commands/processor/resize_dataset.py
@@ -0,0 +1,149 @@
+"""
+Crop images to prepare for training
+"""
+
+import click
+import cv2 as cv
+from PIL import Image, ImageOps, ImageFilter
+
+from app.settings import types
+from app.utils import click_utils
+from app.settings import app_cfg as cfg
+
+cv_resize_algos = {
+  'area': cv.INTER_AREA,
+  'lanco': cv.INTER_LANCZOS4,
+  'linear': cv.INTER_LINEAR,
+  'linear_exact': cv.INTER_LINEAR_EXACT,
+  'nearest': cv.INTER_NEAREST
+}
+"""
+Filter    Q-Down Q-Up   Speed
+NEAREST              ⭐⭐⭐⭐⭐
+BOX       ⭐          ⭐⭐⭐⭐
+BILINEAR  ⭐      ⭐   ⭐⭐⭐
+HAMMING   ⭐⭐         ⭐⭐⭐
+BICUBIC   ⭐⭐⭐   ⭐⭐⭐  ⭐⭐
+LANCZOS   ⭐⭐⭐⭐  ⭐⭐⭐⭐  ⭐
+"""
+pil_resize_algos = {
+  'antialias': Image.ANTIALIAS,
+  'lanczos': Image.LANCZOS,
+  'bicubic': Image.BICUBIC,
+  'hamming': Image.HAMMING,
+  'bileaner': Image.BILINEAR,
+  'box': Image.BOX,
+  'nearest': Image.NEAREST
+  }
+
+@click.command()
+@click.option('--dataset', 'opt_dataset',
+  type=cfg.DatasetVar,
+  required=True,
+  show_default=True,
+  help=click_utils.show_help(types.Dataset))
+@click.option('--store', 'opt_data_store',
+  type=cfg.DataStoreVar,
+  default=click_utils.get_default(types.DataStore.HDD),
+  show_default=True,
+  help=click_utils.show_help(types.Dataset))
+@click.option('-o', '--output', 'opt_dir_out', required=True,
+  help='Output directory')
+@click.option('-e', '--ext', 'opt_glob_ext',
+  default='png', type=click.Choice(['jpg', 'png']),
+  help='File glob ext')
+@click.option('--size', 'opt_size',  
+  type=(int, int), default=(256, 256),
+  help='Output image size max (w,h)')
+@click.option('--interp', 'opt_interp_algo', 
+  type=click.Choice(pil_resize_algos.keys()),
+  default='bicubic',
+  help='Interpolation resizing algorithms')
+@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
+  help='Slice the input list')
+@click.option('-t', '--threads', 'opt_threads', default=8,
+  help='Number of threads')
+@click.option('--recursive/--no-recursive', 'opt_recursive', is_flag=True, default=False,
+  help='Use glob recursion (slower)')
+@click.pass_context
+def cli(ctx, opt_dataset, opt_data_store, opt_dir_out, opt_glob_ext, opt_size, opt_interp_algo,
+  opt_slice, opt_threads, opt_recursive):
+  """Resize dataset images"""
+  
+  import os
+  from os.path import join
+  from pathlib import Path
+  from glob import glob
+  from tqdm import tqdm
+  from multiprocessing.dummy import Pool as ThreadPool
+  from functools import partial
+  import pandas as pd
+  import numpy as np
+
+  from app.utils import logger_utils, file_utils, im_utils
+  from app.models.data_store import DataStore
+
+  # -------------------------------------------------
+  # init
+
+  log = logger_utils.Logger.getLogger()
+
+
+  # -------------------------------------------------
+  # process here
+
+  def pool_resize(fp_in, dir_in, dir_out, im_size, interp_algo):
+    # Threaded image resize function
+    pbar.update(1)
+    try:
+      im = Image.open(fp_in).convert('RGB')
+      im.verify()  # throws error if image is corrupt
+      im.thumbnail(im_size, interp_algo)
+      fp_out = fp_in.replace(dir_in, dir_out)
+      file_utils.mkdirs(fp_out)
+      im.save(fp_out, quality=100)
+    except Exception as e:
+      log.warn(f'Could not open: {fp_in}, Error: {e}')
+      return False
+    return True
+
+
+  data_store = DataStore(opt_data_store, opt_dataset)
+  fp_records = data_store.metadata(types.Metadata.FILE_RECORD)
+  df_records = pd.read_csv(fp_records, dtype=cfg.FILE_RECORD_DTYPES).set_index('index')
+  dir_in = data_store.media_images_original()
+
+  # get list of files to process
+  #fp_ims = file_utils.glob_multi(opt_dir_in, ['jpg', 'png'], recursive=opt_recursive)
+  fp_ims = []
+  for ds_record in df_records.itertuples():
+    fp_im = data_store.face(ds_record.subdir, ds_record.fn, ds_record.ext)
+    fp_ims.append(fp_im)
+
+  if opt_slice:
+    fp_ims = fp_ims[opt_slice[0]:opt_slice[1]]
+  if not fp_ims:
+    log.error('No images. Try with "--recursive"')
+    return
+  log.info(f'processing {len(fp_ims):,} images')
+  
+  # algorithm to use for resizing
+  interp_algo = pil_resize_algos[opt_interp_algo]
+  log.info(f'using {interp_algo} for interpoloation')
+
+  # ensure output dir exists
+  file_utils.mkdirs(opt_dir_out)
+
+  # setup multithreading
+  pbar = tqdm(total=len(fp_ims))
+  # fixed arguments for pool function
+  map_pool_resize = partial(pool_resize, dir_in=dir_in, dir_out=opt_dir_out, im_size=opt_size, interp_algo=interp_algo)
+  #result_list = pool.map(prod_x, data_list)  # simple
+  pool = ThreadPool(opt_threads)
+  # start multithreading
+  with tqdm(total=len(fp_ims)) as pbar:
+    results = pool.map(map_pool_resize, fp_ims)
+  # end multithreading
+  pbar.close()
+
+  log.info(f'Resized: {results.count(True)} / {len(fp_ims)} images')
\ No newline at end of file
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