Name intermediate files sequentially rather than using the input file…

… base name. This guarantees the order is the same as on input, but also allows the user to choose intermediate file format

README.md

@@ -42,14 +42,17 @@ dclib/files/dlib/v18.10/shape_predictor_68_face_landmarks.dat.bz2).
 
 General `pada.py` options:
 
-    $ ./pada.py --help
+    $ pada.py --help
     usage: pada.py [-h] [--debug] [--config CONFIG] [--aligned-path ALIGNED_PATH]
+                   [--aligned-extension ALIGNED_EXTENSION]
                    [--predictor-path PREDICTOR_PATH]
                    [--filtered-files FILTERED_FILES]
-                   {align,framedrop} ...
+                   {print_config_paths,align,framedrop} ...
 
     positional arguments:
-      {align,framedrop}     Sub-command help
+      {print_config_paths,align,framedrop}
+                            Sub-command help
+        print_config_paths  print config paths and exit
         align               align a set of images
         framedrop           Drop frames from a set of images
 
@@ -59,14 +62,16 @@ General `pada.py` options:
       --config CONFIG       Config file path
       --aligned-path ALIGNED_PATH
                             Path where aligned images will be stored
+      --aligned-extension ALIGNED_EXTENSION
+                            Extension (and filetype) to use for aligned images.
       --predictor-path PREDICTOR_PATH
                             DLib face predictor dat file
       --filtered-files FILTERED_FILES
                             File to write filtered files to
 
 `pada.py align` options:
 
-    $ ./pada.py align --help
+    $ pada.py align --help
     usage: pada.py align [-h] [--input-glob INPUT_GLOB] [--img-thresh IMG_THRESH]
 
     optional arguments:
@@ -78,7 +83,7 @@ General `pada.py` options:
 
 `pada.py framedrop` options:
 
-    $ ./pada.py framedrop --help
+    $ pada.py framedrop --help
     usage: pada.py framedrop [-h] [--erode-amount ERODE_AMOUNT]
                              [--frame-skip FRAME_SKIP]
 

examples/pada.conf

@@ -2,7 +2,8 @@
   "global": {
     "aligned_path": "./aligned",
     "predictor_path": "~/shape_predictor_68_face_landmarks.dat",
-    "filtered_files": "filtered.txt"
+    "filtered_files": "filtered.txt",
+    "aligned_extension": "jpg"
   },
   "align": {
     "input_glob": "./input/*.jpg",

make_vid.sh

@@ -23,5 +23,5 @@
 
 mencoder -idx -nosound -noskip -of lavf -lavfopts format=mp4 -ovc x264 \
     -x264encopts pass=1:bitrate=2000:crf=24 -o output.mp4 -mf fps=30 \
-    'mf://@files.txt'
+    'mf://@filtered.txt'
 

pada.py

@@ -46,6 +46,9 @@ def parse_args():
                         default=CONFIG_FILE_NAME)
     parser.add_argument('--aligned-path',
                         help='Path where aligned images will be stored')
+    parser.add_argument('--aligned-extension',
+                        help='Extension (and filetype) to use for aligned '
+                             'images.')
     parser.add_argument('--predictor-path',
                         help='DLib face predictor dat file',
                         type=unicode)
@@ -140,12 +143,15 @@ def parse_args():
         pada.align.align_images(
             input_files=sorted(glob.glob(cfg['input_glob'])),
             out_path=cfg['aligned_path'],
+            out_extension=cfg['aligned_extension'],
             landmark_finder=landmark_finder,
             img_thresh=cfg['img_thresh'])
     elif cli_args.cmd == "framedrop":
+        input_files_glob = os.path.join(
+                                       cfg['aligned_path'],
+                                       '*.{}'.format(cfg['aligned_extension']))
         filtered_files = pada.framedrop.filter_files(
-            input_files=sorted(glob.glob(
-                                  os.path.join(cfg['aligned_path'], '*.jpg'))),
+            input_files=sorted(glob.glob(input_files_glob)),
             frame_skip=cfg['frame_skip'],
             erode_amount=cfg['erode_amount'],
             landmark_finder=landmark_finder)

pada/align.py

@@ -121,7 +121,8 @@ def get_ims_and_landmarks(images, landmark_finder):
     logger.info("Read %s images with landmarks", count)
 
 
-def align_images(input_files, out_path, landmark_finder, img_thresh=0.0):
+def align_images(input_files, out_path, out_extension, landmark_finder,
+                 img_thresh=0.0):
     """
     Align a set of images of a person's face.
 
@@ -134,6 +135,10 @@ def align_images(input_files, out_path, landmark_finder, img_thresh=0.0):
         Directory to write the aligned files to. The output files have the same
         basename as the corresponding input file.
 
+    :param out_extension:
+
+        Extension to use for aligned images.
+
     :param landmark_finder:
 
         An instance of :class:`.LandmarkFinder`, used to find the facial
@@ -155,7 +160,8 @@ def align_images(input_files, out_path, landmark_finder, img_thresh=0.0):
             raise Exception("Path {} exists, but it is not a directory".format(
                                                                      out_path))
         logger.info("%s already exists. Removing existing images.", out_path)
-        for fname in glob.glob(os.path.join(out_path, "*.jpg")):
+        for fname in glob.glob(os.path.join(out_path,
+                                            "*.{}".format(out_extension))):
             os.remove(fname)
     else:
         logger.info("%s does not exist. Creating it.", out_path)
@@ -165,7 +171,7 @@ def align_images(input_files, out_path, landmark_finder, img_thresh=0.0):
     ims_and_landmarks = get_ims_and_landmarks(
                                   read_ims(input_files, img_thresh=img_thresh),
                                   landmark_finder)
-    for n, im, lms in ims_and_landmarks:
+    for idx, (n, im, lms) in enumerate(ims_and_landmarks):
         mask = landmarks.get_face_mask(im.shape, lms)
         masked_im = mask[:, :, numpy.newaxis] * im
         color = ((numpy.sum(masked_im, axis=(0, 1)) /
@@ -177,7 +183,8 @@ def align_images(input_files, out_path, landmark_finder, img_thresh=0.0):
         M = orthogonal_procrustes(ref_landmarks, lms)
         warped = warp_im(im, M, im.shape)
         warped_corrected = warped * ref_color / color
-        out_fname = os.path.join(out_path, os.path.basename(n))
+        out_fname = os.path.join(out_path,
+                                 "{:08d}.{}".format(idx, out_extension))
         cv2.imwrite(out_fname, warped_corrected)
         logger.debug("Wrote file %s", out_fname)
 

pada/framedrop.py

@@ -102,12 +102,15 @@ def filter_files(input_files, frame_skip, erode_amount, landmark_finder):
 
     """
     input_files = list(input_files)
+    logger.info("Filtering %s files", len(input_files))
 
     # Make a mask, which defines the area over which frame difference is
     # measured.
+    logger.debug("Making mask")
     mask = make_mask(input_files[0], erode_amount, landmark_finder)
 
     # Find the nodes in the first and last layer.
+    logger.debug("Finding weights")
     weights = find_weights(input_files, mask, frame_skip)
     sources = input_files[:frame_skip]
     if len(input_files) % frame_skip != 0:
@@ -118,6 +121,7 @@ def filter_files(input_files, frame_skip, erode_amount, landmark_finder):
     # Compute `dist` which gives the minimum distance from any frame to a start
     # frame, and `parent` which given a node returns the previous node on the
     # shortest path to that node.
+    logger.debug("Computing distances")
     dist = {n: (0 if n in sources else None) for n in input_files}
     parent = {}
     for u in input_files: