[PaddleDetection] fix some easy of use problem (#2962)

* fix easy problem

PaddleCV/PaddleDetection/docs/GETTING_STARTED.md

@@ -35,7 +35,7 @@ python tools/train.py -c configs/faster_rcnn_r50_1x.yml
 
 - `-r` or `--resume_checkpoint`: Checkpoint path for resuming training. Such as: `-r output/faster_rcnn_r50_1x/10000`
 - `--eval`: Whether to perform evaluation in training, default is `False`
-- `-p` or `--output_eval`: If perform evaluation in training, this edits evaluation directory, default is current directory.
+- `--output_eval`: If perform evaluation in training, this edits evaluation directory, default is current directory.
 - `-d` or `--dataset_dir`: Dataset path, same as `dataset_dir` of configs. Such as: `-d dataset/coco`
 - `-o`: Set configuration options in config file. Such as: `-o weights=output/faster_rcnn_r50_1x/model_final`
 
@@ -90,7 +90,7 @@ python tools/eval.py -c configs/faster_rcnn_r50_1x.yml
 #### Optional arguments
 
 - `-d` or `--dataset_dir`: Dataset path, same as dataset_dir of configs. Such as: `-d dataset/coco`
-- `-p` or `--output_eval`: Evaluation directory, default is current directory.
+- `--output_eval`: Evaluation directory, default is current directory.
 - `-o`: Set configuration options in config file. Such as: `-o weights=output/faster_rcnn_r50_1x/model_final`
 - `--json_eval`: Whether to eval with already existed bbox.json or mask.json. Default is `False`. Json file directory is assigned by `-f` argument.
 

PaddleCV/PaddleDetection/docs/GETTING_STARTED_cn.md

@@ -36,7 +36,7 @@ python tools/train.py -c configs/faster_rcnn_r50_1x.yml
 
 - `-r` or `--resume_checkpoint`: 从某一检查点恢复训练，例如: `-r output/faster_rcnn_r50_1x/10000`
 - `--eval`: 是否边训练边测试，默认是 `False`
-- `-p` or `--output_eval`: 如果边训练边测试, 这个参数可以编辑评测保存json路径, 默认是当前目录。
+- `--output_eval`: 如果边训练边测试, 这个参数可以编辑评测保存json路径, 默认是当前目录。
 - `-d` or `--dataset_dir`: 数据集路径, 同配置文件里的`dataset_dir`. 例如: `-d dataset/coco`
 - `-o`: 设置配置文件里的参数内容。 例如: `-o weights=output/faster_rcnn_r50_1x/model_final`
 
@@ -84,7 +84,7 @@ python tools/eval.py -c configs/faster_rcnn_r50_1x.yml
 #### 可选参数
 
 - `-d` or `--dataset_dir`: 数据集路径, 同配置文件里的`dataset_dir`。例如: `-d dataset/coco`
-- `-p` or `--output_eval`: 这个参数可以编辑评测保存json路径, 默认是当前目录。
+- `--output_eval`: 这个参数可以编辑评测保存json路径, 默认是当前目录。
 - `-o`: 设置配置文件里的参数内容。 例如: `-o weights=output/faster_rcnn_r50_1x/model_final`
 - `--json_eval`: 是否通过已存在的bbox.json或者mask.json进行评估。默认是`False`。json文件路径通过`-f`指令来设置。
 

PaddleCV/PaddleDetection/ppdet/utils/coco_eval.py

@@ -38,6 +38,7 @@ __all__ = [
     'mask2out',
     'get_category_info',
     'proposal_eval',
+    'cocoapi_eval',
 ]
 
 
@@ -61,22 +62,10 @@ def proposal_eval(results, anno_file, outfile, max_dets=(100, 300, 1000)):
     with open(outfile, 'w') as f:
         json.dump(xywh_results, f)
 
-    coco_gt = COCO(anno_file)
-
-    logger.info("Start evaluate...")
-    coco_dt = coco_gt.loadRes(outfile)
-    coco_ev = COCOeval(coco_gt, coco_dt, 'bbox')
-
-    coco_ev.params.useCats = 0
-    coco_ev.params.maxDets = list(max_dets)
-
-    coco_ev.evaluate()
-    coco_ev.accumulate()
-    coco_ev.summarize()
+    cocoapi_eval(outfile, 'proposal', anno_file=anno_file, max_dets=max_dets)
     # flush coco evaluation result
     sys.stdout.flush()
 
-
 def bbox_eval(results, anno_file, outfile, with_background=True):
     assert 'bbox' in results[0]
     assert outfile.endswith('.json')
@@ -98,12 +87,7 @@ def bbox_eval(results, anno_file, outfile, with_background=True):
     with open(outfile, 'w') as f:
         json.dump(xywh_results, f)
 
-    logger.info("Start evaluate...")
-    coco_dt = coco_gt.loadRes(outfile)
-    coco_ev = COCOeval(coco_gt, coco_dt, 'bbox')
-    coco_ev.evaluate()
-    coco_ev.accumulate()
-    coco_ev.summarize()
+    cocoapi_eval(outfile, 'bbox', coco_gt=coco_gt)
     # flush coco evaluation result
     sys.stdout.flush()
 
@@ -123,12 +107,36 @@ def mask_eval(results, anno_file, outfile, resolution, thresh_binarize=0.5):
     with open(outfile, 'w') as f:
         json.dump(segm_results, f)
 
+    cocoapi_eval(outfile, 'segm', coco_gt=coco_gt)
+
+def cocoapi_eval(jsonfile,
+                 style,
+                 coco_gt=None,
+                 anno_file=None,
+                 max_dets=(100, 300, 1000)):
+    """
+    Args:
+        jsonfile: Evaluation json file, eg: bbox.json, mask.json.
+        style: COCOeval style, can be `bbox` , `segm` and `proposal`.
+        coco_gt: Whether to load COCOAPI through anno_file,
+                 eg: coco_gt = COCO(anno_file)
+        anno_file: COCO annotations file.
+        max_dets: COCO evaluation maxDets.
+    """
+    assert coco_gt != None or anno_file != None
+    if coco_gt == None:
+        coco_gt = COCO(anno_file)
     logger.info("Start evaluate...")
-    coco_dt = coco_gt.loadRes(outfile)
-    coco_ev = COCOeval(coco_gt, coco_dt, 'segm')
-    coco_ev.evaluate()
-    coco_ev.accumulate()
-    coco_ev.summarize()
+    coco_dt = coco_gt.loadRes(jsonfile)
+    if style == 'proposal':
+        coco_eval = COCOeval(coco_gt, coco_dt, 'bbox')
+        coco_eval.params.useCats = 0
+        coco_eval.params.maxDets = list(max_dets)
+    else:
+        coco_eval = COCOeval(coco_gt, coco_dt, style)
+    coco_eval.evaluate()
+    coco_eval.accumulate()
+    coco_eval.summarize()
 
 
 def proposal2out(results, is_bbox_normalized=False):

PaddleCV/PaddleDetection/ppdet/utils/download.py

@@ -76,7 +76,7 @@ def get_dataset_path(path, annotation, image_dir):
     if _dataset_exists(path, annotation, image_dir):
         return path
 
-    logger.info("Dataset {} not exitst, try searching {} or "
+    logger.info("Dataset {} not exists, try searching {} or "
                 "downloading dataset...".format(
                     osp.realpath(path), DATASET_HOME))
 

PaddleCV/PaddleDetection/ppdet/utils/eval_utils.py

@@ -18,12 +18,13 @@ from __future__ import print_function
 
 import logging
 import numpy as np
+import os
 
 import paddle.fluid as fluid
 
 from ppdet.utils.voc_eval import bbox_eval as voc_bbox_eval
 
-__all__ = ['parse_fetches', 'eval_run', 'eval_results']
+__all__ = ['parse_fetches', 'eval_run', 'eval_results', 'json_eval_results']
 
 logger = logging.getLogger(__name__)
 
@@ -96,7 +97,7 @@ def eval_results(results,
                  num_classes,
                  resolution=None,
                  is_bbox_normalized=False,
-                 output_file=None):
+                 output_directory=None):
     """Evaluation for evaluation program results"""
     if metric == 'COCO':
         from ppdet.utils.coco_eval import proposal_eval, bbox_eval, mask_eval
@@ -104,18 +105,18 @@ def eval_results(results,
         with_background = getattr(feed, 'with_background', True)
         if 'proposal' in results[0]:
             output = 'proposal.json'
-            if output_file:
-                output = '{}_proposal.json'.format(output_file)
+            if output_directory:
+                output = os.path.join(output_directory, 'proposal.json')
             proposal_eval(results, anno_file, output)
         if 'bbox' in results[0]:
             output = 'bbox.json'
-            if output_file:
-                output = '{}_bbox.json'.format(output_file)
+            if output_directory:
+                output = os.path.join(output_directory, 'bbox.json')
             bbox_eval(results, anno_file, output, with_background)
         if 'mask' in results[0]:
             output = 'mask.json'
-            if output_file:
-                output = '{}_mask.json'.format(output_file)
+            if output_directory:
+                output = os.path.join(output_directory, 'mask.json')
             mask_eval(results, anno_file, output, resolution)
     else:
         if 'accum_map' in results[-1]:
@@ -124,3 +125,22 @@ def eval_results(results,
         elif 'bbox' in results[0]:
             voc_bbox_eval(
                 results, num_classes, is_bbox_normalized=is_bbox_normalized)
+
+def json_eval_results(feed, metric, json_directory=None):
+    """
+    cocoapi eval with already exists proposal.json, bbox.json or mask.json
+    """
+    assert metric == 'COCO'
+    from ppdet.utils.coco_eval import cocoapi_eval
+    anno_file = getattr(feed.dataset, 'annotation', None)
+    json_file_list = ['proposal.json', 'bbox.json', 'mask.json']
+    if json_directory:
+        for k, v in enumerate(json_file_list):
+            json_file_list[k] = os.path.join(str(json_directory), v)
+
+    coco_eval_style = ['proposal', 'bbox', 'segm']
+    for i, v_json in enumerate(json_file_list):
+        if os.path.exists(v_json):
+            cocoapi_eval(v_json, coco_eval_style[i], anno_file=anno_file)
+        else:
+            logger.info("{} not exists!".format(v_json))

PaddleCV/PaddleDetection/ppdet/utils/stats.py

@@ -55,7 +55,7 @@ class TrainingStats(object):
             for k, v in extras.items():
                 stats[k] = v
         for k, v in self.smoothed_losses_and_metrics.items():
-            stats[k] = round(v.get_median_value(), 6)
+            stats[k] = format(v.get_median_value(), '.6f')
 
         return stats
 

PaddleCV/PaddleDetection/tools/eval.py

@@ -19,9 +19,20 @@ from __future__ import print_function
 import os
 import multiprocessing
 
+def set_paddle_flags(**kwargs):
+    for key, value in kwargs.items():
+        if os.environ.get(key, None) is None:
+            os.environ[key] = str(value)
+
+# NOTE(paddle-dev): All of these flags should be set before
+# `import paddle`. Otherwise, it would not take any effect.
+set_paddle_flags(
+    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
+)
+
 import paddle.fluid as fluid
 
-from ppdet.utils.eval_utils import parse_fetches, eval_run, eval_results
+from ppdet.utils.eval_utils import parse_fetches, eval_run, eval_results, json_eval_results
 import ppdet.utils.checkpoint as checkpoint
 from ppdet.utils.cli import ArgsParser
 from ppdet.utils.check import check_gpu
@@ -78,6 +89,11 @@ def main():
     reader = create_reader(eval_feed, args_path=FLAGS.dataset_dir)
     pyreader.decorate_sample_list_generator(reader, place)
 
+    # eval already exists json file
+    if FLAGS.json_eval:
+        json_eval_results(eval_feed, cfg.metric,
+                json_directory=FLAGS.output_eval)
+        return
     # compile program for multi-devices
     if devices_num <= 1:
         compile_program = fluid.compiler.CompiledProgram(eval_prog)
@@ -115,22 +131,25 @@ def main():
     if 'mask' in results[0]:
         resolution = model.mask_head.resolution
     eval_results(results, eval_feed, cfg.metric, cfg.num_classes, resolution,
-                 is_bbox_normalized, FLAGS.output_file)
-
+                 is_bbox_normalized, FLAGS.output_eval)
 
 if __name__ == '__main__':
     parser = ArgsParser()
     parser.add_argument(
-        "-f",
-        "--output_file",
-        default=None,
-        type=str,
-        help="Evaluation file name, default to bbox.json and mask.json.")
+        "--json_eval",
+        action='store_true',
+        default=False,
+        help="Whether to re eval with already exists bbox.json or mask.json")
     parser.add_argument(
         "-d",
         "--dataset_dir",
         default=None,
         type=str,
         help="Dataset path, same as DataFeed.dataset.dataset_dir")
+    parser.add_argument(
+        "--output_eval",
+        default=None,
+        type=str,
+        help="Evaluation file directory, default is current directory.")
     FLAGS = parser.parse_args()
     main()

PaddleCV/PaddleDetection/tools/infer.py

@@ -22,6 +22,17 @@ import glob
 import numpy as np
 from PIL import Image
 
+def set_paddle_flags(**kwargs):
+    for key, value in kwargs.items():
+        if os.environ.get(key, None) is None:
+            os.environ[key] = str(value)
+
+# NOTE(paddle-dev): All of these flags should be set before
+# `import paddle`. Otherwise, it would not take any effect.
+set_paddle_flags(
+    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
+)
+
 from paddle import fluid
 
 from ppdet.core.workspace import load_config, merge_config, create

PaddleCV/PaddleDetection/tools/train.py

@@ -23,16 +23,13 @@ import numpy as np
 import datetime
 from collections import deque
 
-
 def set_paddle_flags(**kwargs):
     for key, value in kwargs.items():
         if os.environ.get(key, None) is None:
             os.environ[key] = str(value)
 
-
-# NOTE(paddle-dev): All of these flags should be
-# set before `import paddle`. Otherwise, it would
-# not take any effect. 
+# NOTE(paddle-dev): All of these flags should be set before 
+# `import paddle`. Otherwise, it would not take any effect.
 set_paddle_flags(
     FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
 )
@@ -199,7 +196,7 @@ def main():
                 if 'mask' in results[0]:
                     resolution = model.mask_head.resolution
                 eval_results(results, eval_feed, cfg.metric, cfg.num_classes,
-                             resolution, is_bbox_normalized, FLAGS.output_file)
+                             resolution, is_bbox_normalized, FLAGS.output_eval)
 
     train_pyreader.reset()
 
@@ -218,11 +215,10 @@ if __name__ == '__main__':
         default=False,
         help="Whether to perform evaluation in train")
     parser.add_argument(
-        "-f",
-        "--output_file",
+        "--output_eval",
         default=None,
         type=str,
-        help="Evaluation file name, default to bbox.json and mask.json.")
+        help="Evaluation directory, default is current directory.")
     parser.add_argument(
         "-d",
         "--dataset_dir",