Merge branch 'release/1.1.3'

.travis.yml

@@ -18,7 +18,7 @@ install:
     - conda info -a
 
     # Install deps
-    - deps='pip numpy scipy'
+    - deps='pip numpy scipy cython'
     - conda create -q -n pyenv python=$PYTHON pandas=$PANDAS $deps
     - source activate pyenv
     - python -m pip install -U pip

Dockerfile

@@ -0,0 +1,32 @@
+FROM ubuntu:latest 
+
+MAINTAINER Avgerinos Christos <christosavg@gmail.com>
+
+#ARG GT_DIR
+#ARG TEST_DIR
+
+RUN apt-get update \
+  && apt-get install -y python3-pip python3-dev vim \
+  && cd /usr/local/bin \
+  && ln -s /usr/bin/python3 python \
+  && pip3 install --upgrade pip
+
+RUN pip3 install --no-cache-dir numpy scipy
+RUN pip install -Iv pandas==0.21.0
+RUN mkdir -p /motmetrics/py-motmetrics
+RUN mkdir -p /motmetrics/2DMOT2015
+
+COPY ./py-motmetrics /motmetrics/py-motmetrics
+COPY ./data /motmetrics/data
+
+#RUN pip install motmetrics
+RUN pip install -e ./motmetrics/py-motmetrics/
+
+#RUN pip install -r motmetrics/py-motmetrics/requirements.txt
+
+ENV GT_DIR motmetrics/data/train/
+ENV TEST_DIR motmetrics/data/test/
+
+#ENTRYPOINT python3 -m motmetrics.apps.eval_motchallenge motmetrics/data/train/ motmetrics/data/test/ && /bin/bash
+CMD ["sh", "-c", "python3 -m motmetrics.apps.eval_motchallenge ${GT_DIR} ${TEST_DIR} && /bin/bash"]
+

Readme.md

@@ -1,3 +1,5 @@
+
+
 [![PyPI version](https://badge.fury.io/py/motmetrics.svg)](https://badge.fury.io/py/motmetrics) [![](https://travis-ci.org/cheind/py-motmetrics.svg?branch=master)](https://travis-ci.org/cheind/py-motmetrics)
 
 ## py-motmetrics
@@ -425,6 +427,23 @@ EURASIP Journal on Image and Video Processing 2008.1 (2008): 1-10.
 Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. IEEE, 2009.
 4. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. E. Ristani, F. Solera, R. S. Zou, R. Cucchiara and C. Tomasi. ECCV 2016 Workshop on Benchmarking Multi-Target Tracking.
 
+### Docker 
+
+#### Update ground truth and test data:
+/data/train directory should contain MOT 2D 2015 Ground Truth files. 
+/data/test directory should contain your results.
+
+You can check usage and directory listing at 
+https://github.com/cheind/py-motmetrics/blob/master/motmetrics/apps/eval_motchallenge.py
+
+#### Build Image
+docker build -t desired-image-name -f Dockerfile .
+
+#### Run Image
+docker run desired-image-name
+
+(credits to [christosavg](https://github.com/christosavg))
+
 ### License
 
 ```

Release.md

@@ -8,7 +8,7 @@
     - [pip install lapsolver]
     - pip install .
     - pytest
-    - deactivate motmetrics-env
+    - deactivate
     - conda env remove -n motmetrics-env
     - git add, commit
     - git flow release finish <VERSION>

appveyor.yml

@@ -24,7 +24,7 @@ install:
   - conda config --set always_yes yes
   - conda update -q conda
   - conda config --set auto_update_conda no
-  - conda install -q pip pytest numpy
+  - conda install -q pip pytest numpy cython
   - python -m pip install -U pip
   - pip install wheel
   - pip install --upgrade --ignore-installed setuptools

motmetrics/__init__.py

@@ -8,4 +8,4 @@
 
 
 # Needs to be last line
-__version__ = '1.1.2'
+__version__ = '1.1.3'

motmetrics/mot.py

@@ -245,8 +245,8 @@ def new_event_dataframe():
         df = pd.DataFrame(
             OrderedDict([
                 ('Type', pd.Series(cats)),          # Type of event. One of FP (false positive), MISS, SWITCH, MATCH
-                ('OId', pd.Series(dtype=str)),      # Object ID or -1 if FP. Using float as missing values will be converted to NaN anyways.
-                ('HId', pd.Series(dtype=str)),      # Hypothesis ID or NaN if MISS. Using float as missing values will be converted to NaN anyways.
+                ('OId', pd.Series(dtype=object)),      # Object ID or -1 if FP. Using float as missing values will be converted to NaN anyways.
+                ('HId', pd.Series(dtype=object)),      # Hypothesis ID or NaN if MISS. Using float as missing values will be converted to NaN anyways.
                 ('D', pd.Series(dtype=float)),      # Distance or NaN when FP or MISS            
             ]),
             index=idx
@@ -271,8 +271,8 @@ def new_event_dataframe_with_data(indices, events):
         raw_type = pd.Categorical(tevents[0], categories=['RAW', 'FP', 'MISS', 'SWITCH', 'MATCH'], ordered=False)
         series = [
             pd.Series(raw_type, name='Type'),
-            pd.Series(tevents[1], dtype=str, name='OId'),
-            pd.Series(tevents[2], dtype=str, name='HId'),
+            pd.Series(tevents[1], dtype=object, name='OId'),
+            pd.Series(tevents[2], dtype=object, name='HId'),
             pd.Series(tevents[3], dtype=float, name='D')
         ]
 

motmetrics/tests/test_mot.py

@@ -54,7 +54,8 @@ def test_events():
     expect.loc[(4, 5), :] = ['MATCH', 2, 'b', 5.]
     # frame 5 generates no events
 
-    assert pd.DataFrame.equals(acc.events, expect)
+    from pandas.util.testing import assert_frame_equal
+    assert_frame_equal(acc.events, expect)
 
 
 def test_max_switch_time():
@@ -115,9 +116,10 @@ def test_merge_dataframes():
     acc.update([1, 2], ['a', 'b'], [[1, 0.5], [0.3, 1]], frameid=2)
     acc.update([1, 2], ['a', 'b'], [[0.2, np.nan], [np.nan, 0.1]], frameid=3)
 
-    r, mappings = mm.MOTAccumulator.merge_event_dataframes([acc.events, acc.events], return_mappings=True)
+    r, mappings = mm.MOTAccumulator.merge_event_dataframes([acc.events, acc.events], return_mappings=True)    
 
     expect = mm.MOTAccumulator.new_event_dataframe()
+
     expect.loc[(0, 0), :] = ['RAW', np.nan, mappings[0]['hid_map']['a'], np.nan]
     expect.loc[(0, 1), :] = ['RAW', np.nan, mappings[0]['hid_map']['b'], np.nan]
     expect.loc[(0, 2), :] = ['FP', np.nan, mappings[0]['hid_map']['a'], np.nan]
@@ -143,7 +145,6 @@ def test_merge_dataframes():
     expect.loc[(3, 5), :] = ['SWITCH', mappings[0]['oid_map'][2], mappings[0]['hid_map']['b'], 0.1]
 
     # Merge duplication
-
     expect.loc[(4, 0), :] = ['RAW', np.nan, mappings[1]['hid_map']['a'], np.nan]
     expect.loc[(4, 1), :] = ['RAW', np.nan, mappings[1]['hid_map']['b'], np.nan]
     expect.loc[(4, 2), :] = ['FP', np.nan, mappings[1]['hid_map']['a'], np.nan]
@@ -167,5 +168,7 @@ def test_merge_dataframes():
     expect.loc[(7, 3), :] = ['RAW', mappings[1]['oid_map'][2], mappings[1]['hid_map']['b'], 0.1]            
     expect.loc[(7, 4), :] = ['SWITCH', mappings[1]['oid_map'][1], mappings[1]['hid_map']['a'], 0.2]
     expect.loc[(7, 5), :] = ['SWITCH', mappings[1]['oid_map'][2], mappings[1]['hid_map']['b'], 0.1]
+
+    from pandas.util.testing import assert_frame_equal
+    assert_frame_equal(r, expect)
 
-    assert pd.DataFrame.equals(r, expect)

requirements.txt

@@ -1,3 +1,3 @@
 numpy>=1.12.1
-pandas>=0.19.2
+pandas>=0.23.1
 scipy>=0.19.0