      """ Return a path to a folder, creating it if it doesn't exist """
      logger.debug("Requested path: '%s'", path)
      output_dir = Path(path)
      output_dir.mkdir(parents=True, exist_ok=True)
      logger.debug("Returning: '%s'", output_dir)
      return output_dir
  
  
 
</s> remove def get_folder(path):
 </s> add def get_folder(path, make_folder=True): </s> remove         for idx, face in enumerate(detected_faces):
            detected_face = DetectedFace()
            detected_face.from_dlib_rect(face)
            detected_face.landmarksXY = landmarks[idx]
            final_faces.append(detected_face)
        return final_faces
 </s> add     def get_detected_faces(self, filename, image, extract_queue):
        """ Return detected faces from alignments or detector """
        logger.trace("Getting faces for: '%s'", filename)
        if not self.extractor:
            detected_faces = self.alignments_faces(os.path.basename(filename), image)
        else:
            detected_faces = self.detect_faces(extract_queue, filename, image)
        logger.trace("Got %s faces for: '%s'", len(detected_faces), filename)
        return detected_faces </s> remove                 if self.args.draw_transparent:
                    filename = "{}.png".format(os.path.splitext(filename)[0])
                    logger.trace("Set extension to png: `%s`", filename)
 </s> add     def get_trainer(self, model_dir):
        """ Return the trainer name if provided, or read from state file """
        if self.args.trainer:
            logger.debug("Trainer name provided: '%s'", self.args.trainer)
            return self.args.trainer

        statefile = [fname for fname in os.listdir(str(model_dir))
                     if fname.endswith("_state.json")]
        if len(statefile) != 1:
            logger.error("There should be 1 state file in your model folder. %s were found. "
                         "Specify a trainer with the '-t', '--trainer' option.")
            exit(1)
        statefile = os.path.join(str(model_dir), statefile[0])

        with open(statefile, "rb") as inp:
            state = self.serializer.unmarshal(inp.read().decode("utf-8"))
            trainer = state.get("name", None)

        if not trainer:
            logger.error("Trainer name could not be read from state file. "
                         "Specify a trainer with the '-t', '--trainer' option.")
            exit(1)
        logger.debug("Trainer from state file: '%s'", trainer)
        return trainer

    def predict_faces(self):
        """ Get detected faces from images """
        faces_seen = 0
        batch = list()
        while True:
            item = self.in_queue.get()
            if item != "EOF":
                logger.trace("Got from queue: '%s'", item["filename"])
                faces_count = len(item["detected_faces"])
                if faces_count != 0:
                    self.pre_process.do_actions(item)
                    self.faces_count += faces_count
                if faces_count > 1:
                    self.verify_output = True
                    logger.verbose("Found more than one face in an image! '%s'",
                                   os.path.basename(item["filename"]))

                self.load_aligned(item)

                faces_seen += faces_count
                batch.append(item)

            if faces_seen < self.batchsize and item != "EOF":
                logger.trace("Continuing. Current batchsize: %s", faces_seen)
                continue </s> remove         logger.info("Loading config: '%s'", self.configfile)
 </s> add         logger.verbose("Loading config: '%s'", self.configfile)
    if not make_folder and not output_dir.exists():
        logger.debug("%s does not exist", path)
        return None
      """ Return a path to a folder, creating it if it doesn't exist """
      logger.debug("Requested path: '%s'", path)
      output_dir = Path(path)
    if not make_folder and not output_dir.exists():
        logger.debug("%s does not exist", path)
        return None
      output_dir.mkdir(parents=True, exist_ok=True)
      logger.debug("Returning: '%s'", output_dir)
      return output_dir
  
  
keep keep add keep keep keep keep keep
 Convert refactor (#703)

* Separate predict and implement pool

* Add check and raise error to multithreading

Box functions to config. Add crop box option.

* All masks to mask module. Refactor convert masks

Predicted mask passed from model. Cli update

* Intesect box with mask and fixes

* Use raw NN output for convert

Use raw mask for face adjustments. Split adjustments to pre and post warp

* Separate out adjustments. Add unmask sharpen

* Set sensible defaults. Pre PR Testing

* Fix queue sizes. Move masked.py to lib

* Fix Skip Frames. Fix GUI Config popup

* Sensible queue limits. Add a less resource intensive single processing mode

* Fix predicted mask. Amend smooth box defaults

* Deterministic ordering for video output

* Video to Video convert implemented

* Fixups

- Remove defaults from folders across all stages
- Move match-hist and aca into color adjustments selectable
- Handle crashes properly for pooled processes
- Fix output directory does not exist error when creating a new output folder
- Force output to frames if input is not a video

* Add Color Transfer adjustment method

Wrap info text in GUI plugin configure popup

* Refactor image adjustments. Easier to create plugins

Start implementing config options for video encoding

* Add video encoding config options

Allow video encoding for frames input (must pass in a reference video)
Move video and image output writers to plugins

* Image writers config options

Move scaling to cli
Move draw_transparent to images config
Add config options for cv2 writer
Add Pillow image writer

* Add gif filetype to Pillow. Fix draw transparent for Pillow

* Add Animated GIF writer

standardize opencv/pillow defaults

* [speedup] Pre-encode supported writers in the convert pool (opencv, pillow)

Move scaling to convert pool
Remove dfaker mask

* Fix default writer

* Bugfixes

* Better custom argparse formatting 
lib/utils.py