restruct folders (#71)

.gitignore

@@ -17,7 +17,6 @@ __pycache__
 /cmake-build
 /coco
 /data
-/models
 /tensorlayer
 /vis
 cmake_install.cmake
@@ -29,7 +28,6 @@ CTestTestfile.cmake
 inference/*png
 libstdtensor-prefix
 libstdtracer-prefix
-models_hao*
 test.py
 test.py
 Testing

.travis.yml

@@ -22,7 +22,7 @@ before_install:
 script:
 - docker build --rm -t openpose-plus-test:snapshot -f docker/Dockerfile.builder-cpu-bionic .
 - docker run --rm -it openpose-plus-test:snapshot sh -c './configure && make && make test'
-- python ./test_inference.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=vgg
-- python ./test_inference.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=vggtiny
-- python ./test_inference.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=mobilenet
-- python ./test_inference.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=hao28_experimental
+- python ./examples/example-inference-1.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=vgg
+- python ./examples/example-inference-1.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=vggtiny
+- python ./examples/example-inference-1.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=mobilenet
+- python ./examples/example-inference-1.py --path-to-npz='' --images=$(ls data/media/*.jpg | sort | head -n 3 | tr '\n' ',') --base-model=hao28_experimental

test_inference.py → examples/example-inference-1.py

@@ -8,9 +8,11 @@
 import tensorflow as tf
 import tensorlayer as tl
 
-from inference.common import measure, plot_humans, read_imgfile
-from inference.estimator2 import TfPoseEstimator as TfPoseEstimator2
-from models import get_model
+sys.path.append('.')
+
+from openpose_plus.inference.common import measure, plot_humans, read_imgfile
+from openpose_plus.inference.estimator2 import TfPoseEstimator as TfPoseEstimator2
+from openpose_plus.models import get_model
 
 tf.logging.set_verbosity(tf.logging.INFO)
 tl.logging.set_verbosity(tl.logging.INFO)

test_inference-2.py → examples/example-inference-2.py

@@ -10,8 +10,10 @@
 import tensorflow as tf
 import tensorlayer as tl
 
-from inference.common import measure, plot_humans, read_imgfile
-from inference.estimator2 import TfPoseEstimator as TfPoseEstimator2
+sys.path.append('.')
+
+from openpose_plus.inference.common import measure, plot_humans, read_imgfile, load_graph
+from openpose_plus.inference.estimator2 import TfPoseEstimator as TfPoseEstimator2
 
 
 class TfPoseEstimator2Loader(TfPoseEstimator2):

inference/estimator2.py → openpose_plus/inference/estimator2.py

@@ -4,7 +4,7 @@
 import tensorflow as tf
 import tensorlayer as tl
 
-from inference.post_process import PostProcessor
+from .post_process import PostProcessor
 
 logger = logging.getLogger('TfPoseEstimator')
 logger.setLevel(logging.DEBUG)
@@ -33,10 +33,10 @@ def __del__(self):
         self.persistent_sess.close()
 
     def inference(self, npimg):
-        heatmap, pafmap = self.persistent_sess.run([self.tensor_heatmap, self.tensor_paf],
-                                                   feed_dict={
-                                                       self.tensor_image: [npimg],
-                                                   })
+        heatmap, pafmap = self.persistent_sess.run(
+            [self.tensor_heatmap, self.tensor_paf], feed_dict={
+                self.tensor_image: [npimg],
+            })
 
         t = time.time()
         humans, heatmap_up, pafmap_up = self.post_processor(heatmap[0], pafmap[0])

inference/post_process.py → openpose_plus/inference/post_process.py

@@ -2,8 +2,8 @@
 import scipy.stats as st
 import tensorflow as tf
 
-from inference import common
-from inference.common import CocoPart
+from . import common
+from .common import CocoPart
 
 
 def _normalize(t):
@@ -82,7 +82,7 @@ def __repr__(self):
 
 
 def estimate_paf(peaks, heat_mat, paf_mat):
-    from inference.pafprocess import pafprocess  # TODO: don't depend on it
+    from .pafprocess import pafprocess  # TODO: don't depend on it
     pafprocess.process_paf(peaks, heat_mat, paf_mat)
 
     humans = []
@@ -141,11 +141,12 @@ def __call__(self, heatmap_input, pafmap_input):
             heatmap_input = heatmap_input.transpose(p)
             pafmap_input = pafmap_input.transpose(p)
 
-        peaks, heatmap, pafmap = self.sess.run([self.peaks, self.heapmap_upsample, self.paf_upsample],
-                                               feed_dict={
-                                                   self.heatmap_input: [heatmap_input],
-                                                   self.paf_input: [pafmap_input],
-                                               })
+        peaks, heatmap, pafmap = self.sess.run(
+            [self.peaks, self.heapmap_upsample, self.paf_upsample],
+            feed_dict={
+                self.heatmap_input: [heatmap_input],
+                self.paf_input: [pafmap_input],
+            })
 
         humans = estimate_paf(peaks[0], heatmap[0], pafmap[0])
         return humans, heatmap[0], pafmap[0]

models.py → openpose_plus/models/__init__.py

@@ -1,6 +1,7 @@
 import tensorflow as tf
-from config import config
-from inference.common import rename_tensor
+
+from ..config import config
+from ..inference.common import rename_tensor
 
 __all__ = [
     'get_base_model',
@@ -22,13 +23,13 @@ def _input_image(height, width, data_format, name):
 
 def get_base_model(name):
     if name == 'vgg':
-        from models_vgg import model
+        from .models_vgg import model
     elif name == 'vggtiny':
-        from models_vggtiny import model
+        from .models_vggtiny import model
     elif name == 'mobilenet':
-        from models_mobilenet import model
+        from .models_mobilenet import model
     elif name == 'hao28_experimental':
-        from models_hao28_experimental import model
+        from .models_hao28_experimental import model
     else:
         raise RuntimeError('unknown base model %s' % name)
     return model

scripts/install-pafprocess.sh

@@ -1,7 +1,7 @@
 #!/bin/sh
 set -e
 
-cd $(dirname $0)/../inference
+cd $(dirname $0)/../openpose_plus/inference
 
 [ ! -d pafprocess ] && svn export https://github.com/ildoonet/tf-pose-estimation/trunk/tf_pose/pafprocess
 cd pafprocess

scripts/profile.sh

@@ -22,7 +22,7 @@ export PYTHONUNBUFFERED=1
 MODEL_DIR=${HOME}/Downloads
 DATA_DIR=$HOME/var/data/openpose
 
-IMAGES=$(ls ${DATA_DIR}/examples/media/*.png | sort | tr '\n' ',')
+IMAGES=$(ls ${DATA_DIR}/examples/media/*.jpg | sort | tr '\n' ',')
 
 REPEAT=10
 LIMIT=1
@@ -41,7 +41,7 @@ profile_model() {
         return
     fi
 
-    ./test_inference.py --path-to-npz=${MODEL_DIR}/$npz \
+    ./examples/example-inference-1.py --path-to-npz=${MODEL_DIR}/$npz \
         --base-model=$model \
         --images=${IMAGES} \
         --data-format=$data_format \
@@ -51,10 +51,10 @@ profile_model() {
 }
 
 mkdir -p logs
-# measure profile_model vggtiny new-models/hao18/pose350000.npz NHWC
+measure profile_model vggtiny new-models/hao18/pose350000.npz NHWC
 # measure profile_model vggtiny new-models/hao18/pose350000.npz NCHW
 # measure profile_model mobilenet mbn280000.npz NHWC
 # measure profile_model vgg vgg450000_no_cpm.npz NHWC
 # measure profile_model vgg vgg450000_no_cpm.npz NCHW
 # measure profile_model hao28_experimental hao28/pose345000.npz NHWC
-measure profile_model hao28_experimental hao28/pose345000.npz NCHW
+# measure profile_model hao28_experimental hao28/pose345000.npz NCHW