diff options
Diffstat (limited to 'megapixels/commands/cv')
| -rw-r--r-- | megapixels/commands/cv/face_attributes.py | 19 | ||||
| -rw-r--r-- | megapixels/commands/cv/face_pose.py | 2 | ||||
| -rw-r--r-- | megapixels/commands/cv/face_roi.py | 61 | ||||
| -rw-r--r-- | megapixels/commands/cv/face_vector.py | 3 | ||||
| -rw-r--r-- | megapixels/commands/cv/resize.py | 13 | ||||
| -rw-r--r-- | megapixels/commands/cv/resize_dataset.py | 149 |
6 files changed, 204 insertions, 43 deletions
diff --git a/megapixels/commands/cv/face_attributes.py b/megapixels/commands/cv/face_attributes.py index bb7978f7..01fe3bd1 100644 --- a/megapixels/commands/cv/face_attributes.py +++ b/megapixels/commands/cv/face_attributes.py @@ -77,7 +77,7 @@ def cli(ctx, opt_fp_in, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, # ------------------------------------------------------------------------- # load filepath data fp_record = data_store.metadata(types.Metadata.FILE_RECORD) - df_record = pd.read_csv(fp_record, dtype={'fn':str}).set_index('index') + df_record = pd.read_csv(fp_record, dtype=cfg.FILE_RECORD_DTYPES).set_index('index') # load ROI data fp_roi = data_store.metadata(types.Metadata.FACE_ROI) df_roi = pd.read_csv(fp_roi).set_index('index') @@ -112,18 +112,15 @@ def cli(ctx, opt_fp_in, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, bbox_norm = BBox.from_xywh(df_img.x, df_img.y, df_img.w, df_img.h) bbox_dim = bbox_norm.to_dim(dim) - #age_apnt = age_estimator_apnt.predict(im_resized, bbox_norm) - #age_real = age_estimator_real.predict(im_resized, bbox_norm) - #gender = gender_estimator.predict(im_resized, bbox_norm) + age_apnt = age_estimator_apnt.predict(im_resized, bbox_norm) + age_real = age_estimator_real.predict(im_resized, bbox_norm) + gender = gender_estimator.predict(im_resized, bbox_norm) - # attr_obj = { - # 'age_real':float(f'{age_real:.2f}'), - # 'age_apparent': float(f'{age_apnt:.2f}'), - # 'm': float(f'{gender["m"]:.4f}'), - # 'f': float(f'{gender["f"]:.4f}'), - # 'roi_index': roi_index - # } attr_obj = { + 'age_real':float(f'{age_real:.2f}'), + 'age_apparent': float(f'{age_apnt:.2f}'), + 'm': float(f'{gender["m"]:.4f}'), + 'f': float(f'{gender["f"]:.4f}'), 'roi_index': roi_index } results.append(attr_obj) diff --git a/megapixels/commands/cv/face_pose.py b/megapixels/commands/cv/face_pose.py index 75db603b..cb7ec56c 100644 --- a/megapixels/commands/cv/face_pose.py +++ b/megapixels/commands/cv/face_pose.py @@ -92,7 +92,7 @@ def cli(ctx, opt_fp_in, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, # load data fp_record = data_store.metadata(types.Metadata.FILE_RECORD) - df_record = pd.read_csv(fp_record, dtype={'fn':str}).set_index('index') + df_record = pd.read_csv(fp_record, dtype=cfg.FILE_RECORD_DTYPES).set_index('index') # load ROI data fp_roi = data_store.metadata(types.Metadata.FACE_ROI) df_roi = pd.read_csv(fp_roi).set_index('index') diff --git a/megapixels/commands/cv/face_roi.py b/megapixels/commands/cv/face_roi.py index 950936cf..e83b0f61 100644 --- a/megapixels/commands/cv/face_roi.py +++ b/megapixels/commands/cv/face_roi.py @@ -105,23 +105,29 @@ def cli(ctx, opt_fp_in, opt_dir_media, opt_fp_out, opt_data_store, opt_dataset, # get list of files to process - fp_in = data_store.metadata(types.Metadata.FILE_RECORD) if opt_fp_in is None else opt_fp_in - df_records = pd.read_csv(fp_in, dtype={'fn':str}).set_index('index') + fp_record = data_store.metadata(types.Metadata.FILE_RECORD) if opt_fp_in is None else opt_fp_in + df_record = pd.read_csv(fp_record, dtype=cfg.FILE_RECORD_DTYPES).set_index('index') if opt_slice: - df_records = df_records[opt_slice[0]:opt_slice[1]] - log.debug('processing {:,} files'.format(len(df_records))) + df_record = df_record[opt_slice[0]:opt_slice[1]] + log.debug('processing {:,} files'.format(len(df_record))) # filter out grayscale color_filter = color_filters[opt_color_filter] # set largest flag, to keep all or only largest - opt_largest = opt_largest == 'largest' + opt_largest = (opt_largest == 'largest') data = [] + skipped_files = [] + processed_files = [] - for df_record in tqdm(df_records.itertuples(), total=len(df_records)): + for df_record in tqdm(df_record.itertuples(), total=len(df_record)): fp_im = data_store.face(str(df_record.subdir), str(df_record.fn), str(df_record.ext)) - im = cv.imread(fp_im) - im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1]) + try: + im = cv.imread(fp_im) + im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1]) + except Exception as e: + log.debug(f'could not read: {fp_im}') + return # filter out color or grayscale iamges if color_filter != color_filters['all']: try: @@ -134,31 +140,38 @@ def cli(ctx, opt_fp_in, opt_dir_media, opt_fp_out, opt_data_store, opt_dataset, continue try: - bboxes = detector.detect(im_resized, pyramids=opt_pyramids, largest=opt_largest, + bboxes_norm = detector.detect(im_resized, pyramids=opt_pyramids, largest=opt_largest, zone=opt_zone, conf_thresh=opt_conf_thresh) except Exception as e: log.error('could not detect: {}'.format(fp_im)) log.error('{}'.format(e)) continue - for bbox in bboxes: - roi = { - 'record_index': int(df_record.Index), - 'x': bbox.x, - 'y': bbox.y, - 'w': bbox.w, - 'h': bbox.h - } - data.append(roi) - if len(bboxes) == 0: + if len(bboxes_norm) == 0: + skipped_files.append(fp_im) log.warn(f'no faces in: {fp_im}') - + log.warn(f'skipped: {len(skipped_files)}. found:{len(processed_files)} files') + else: + processed_files.append(fp_im) + for bbox in bboxes_norm: + roi = { + 'record_index': int(df_record.Index), + 'x': bbox.x, + 'y': bbox.y, + 'w': bbox.w, + 'h': bbox.h + } + data.append(roi) + # if display optined - if opt_display and len(bboxes): + if opt_display and len(bboxes_norm): # draw each box - for bbox in bboxes: - bbox_dim = bbox.to_dim(im_resized.shape[:2][::-1]) - draw_utils.draw_bbox(im_resized, bbox_dim) + for bbox_norm in bboxes_norm: + dim = im_resized.shape[:2][::-1] + bbox_dim = bbox.to_dim(dim) + if dim[0] > 1000: + im_resized = im_utils.resize(im_resized, width=1000) + im_resized = draw_utils.draw_bbox(im_resized, bbox_norm) # display and wait cv.imshow('', im_resized) diff --git a/megapixels/commands/cv/face_vector.py b/megapixels/commands/cv/face_vector.py index 9a527bc3..cb155d08 100644 --- a/megapixels/commands/cv/face_vector.py +++ b/megapixels/commands/cv/face_vector.py @@ -88,7 +88,7 @@ def cli(ctx, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, opt_size, # load data fp_record = data_store.metadata(types.Metadata.FILE_RECORD) - df_record = pd.read_csv(fp_record, dtype={'fn':str}).set_index('index') + df_record = pd.read_csv(fp_record, dtype=cfg.FILE_RECORD_DTYPES).set_index('index') fp_roi = data_store.metadata(types.Metadata.FACE_ROI) df_roi = pd.read_csv(fp_roi).set_index('index') @@ -107,6 +107,7 @@ def cli(ctx, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, opt_size, ds_record = df_record.iloc[record_index] fp_im = data_store.face(ds_record.subdir, ds_record.fn, ds_record.ext) im = cv.imread(fp_im) + im = im_utils.resize(im, width=opt_size[0], height=opt_size[1]) for roi_index, df_img in df_img_group.iterrows(): # get bbox x, y, w, h = df_img.x, df_img.y, df_img.w, df_img.h diff --git a/megapixels/commands/cv/resize.py b/megapixels/commands/cv/resize.py index dcd621b3..7409ee6f 100644 --- a/megapixels/commands/cv/resize.py +++ b/megapixels/commands/cv/resize.py @@ -49,7 +49,7 @@ centerings = { help='File glob ext') @click.option('--size', 'opt_size', type=(int, int), default=(256, 256), - help='Output image size (square)') + help='Max output size') @click.option('--method', 'opt_scale_method', type=click.Choice(methods.keys()), default='lanczos', @@ -88,7 +88,7 @@ def cli(ctx, opt_dir_in, opt_dir_out, opt_glob_ext, opt_size, opt_scale_method, # ------------------------------------------------- # process here - def pool_resize(fp_im, opt_size, scale_method, centering): + def pool_resize(fp_im, opt_size, scale_method): # Threaded image resize function try: pbar.update(1) @@ -100,7 +100,7 @@ def cli(ctx, opt_dir_in, opt_dir_out, opt_glob_ext, opt_size, opt_scale_method, log.error(e) return False - im = ImageOps.fit(im, opt_size, method=scale_method, centering=centering) + #im = ImageOps.fit(im, opt_size, method=scale_method, centering=centering) if opt_equalize: im_np = im_utils.pil2np(im) @@ -117,8 +117,8 @@ def cli(ctx, opt_dir_in, opt_dir_out, opt_glob_ext, opt_size, opt_scale_method, except: return False - centering = centerings[opt_center] - scale_method = methods[opt_scale_method] + #centering = centerings[opt_center] + #scale_method = methods[opt_scale_method] # get list of files to process fp_ims = glob(join(opt_dir_in, '*.{}'.format(opt_glob_ext))) @@ -132,7 +132,8 @@ def cli(ctx, opt_dir_in, opt_dir_out, opt_glob_ext, opt_size, opt_scale_method, # setup multithreading pbar = tqdm(total=len(fp_ims)) - pool_resize = partial(pool_resize, opt_size=opt_size, scale_method=scale_method, centering=centering) + #pool_resize = partial(pool_resize, opt_size=opt_size, scale_method=scale_method, centering=centering) + pool_resize = partial(pool_resize, opt_size=opt_size) #result_list = pool.map(prod_x, data_list) pool = ThreadPool(opt_threads) with tqdm(total=len(fp_ims)) as pbar: diff --git a/megapixels/commands/cv/resize_dataset.py b/megapixels/commands/cv/resize_dataset.py new file mode 100644 index 00000000..3a6ec15f --- /dev/null +++ b/megapixels/commands/cv/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 |