[~] Refactor

d1/mlb_player_v5.py

@@ -0,0 +1,53 @@
+! pip install pyyaml==5.2
+! pip install scipy==1.1.0
+! pip install torch==1.2.0 torchvision==0.4.0
+! pip install pillow==6.2.2
+import torch
+print(torch.__version__)
+import yaml, scipy
+print(yaml.__version__)
+print(scipy.__version__)
+
+!rm -rf /kaggle/working/AlphaPose
+os.chdir('/kaggle/working/')
+!git clone https://github.com/MVIG-SJTU/AlphaPose.git
+    
+!python -m pip install cython
+!apt-get install libyaml-dev
+
+import os
+os.chdir('/kaggle/working/AlphaPose')
+print(os.getcwd())
+! python setup.py build develop
+
+import gdown
+import os
+for o1, o2 in [
+    (
+        '1D47msNOOiJKvPOXlnpyzdKA3k6E97NTC',
+        '/kaggle/working/AlphaPose/detector/yolo/data/yolov3-spp.weights',
+    ),
+    (
+        '1nlnuYfGNuHWZztQHXwVZSL_FvfE551pA',
+        '/kaggle/working/AlphaPose/detector/tracker/data/JDE-1088x608-uncertainty',
+    ),
+    (
+        '1kQhnMRURFiy7NsdS8EFL-8vtqEXOgECn',
+        '/kaggle/working/AlphaPose/pretrained_models/fast_res50_256x192.pth'
+    ),
+]:
+    os.makedirs(os.path.split(o2)[0], exist_ok=True)
+    gdown.download(
+        'https://drive.google.com/u/0/uc?export=download&confirm=f_Ix&id=%s' % o1,
+        o2,
+        quiet=False
+    )
+
+    
+import os
+os.chdir('/kaggle/working/AlphaPose')
+! ls
+! python3 scripts/demo_inference.py --cfg configs/coco/resnet/256x192_res50_lr1e-3_1x.yaml --checkpoint pretrained_models/fast_res50_256x192.pth --indir examples/demo/ --save_img
+# result json and rendered images are saved here:
+! ls examples/res/
+! ls examples/res/vis

python/tasks/mlb_player.py

@@ -1095,7 +1095,7 @@ def kernel_15(
             )
 
             t32 = o_14['o_7']['estimate_pose'](
-                t13,
+                t12,
                 scale_param=[1.0],
                 display=False,
             )