Repository: open-mmlab/mmpose

Issue:
Ｈow  to test on an image and get the whole body result (an image with whole body pose estimation)?
Ｈow  to test on an image and get the whole body result (an image with whole body pose estimation)?


Discussion:
Please refer to the topdown demo.
thanks!


I have run the demo like this ,but  got the result that without the whole body pose estimation, what's wrong with my run code?

`python demo/top_down_img_demo.py     configs/top_down/hrnet/coco-wholebody/hrnet_w48_coco_wholebody_256x192.py     checkpoints/hrnet_w48-8ef0771d.pth     --img-root tests/data/coco/ --json-file tests/data/coco/test_coco_wholebody.json     --out-img-root vis_results
`

![vis_0](https://user-images.githubusercontent.com/45363047/93962946-8a8e8200-fd8e-11ea-843e-649b0215144b.jpg)

the result is showed above, hope for you answer,thanks very much!
have you solved it?
![vis_0](https://user-images.githubusercontent.com/45363047/93984894-f7b60d80-fdb6-11ea-8354-a7ce5d1a10ed.jpg)

Thank you, I have solved it, the result is shown above, but there is another problem that the line of hand and face is too thick, may I ask how to adjust the thickness of the line of hand and face?

Resolving patch:
diff --git a/mmpose/apis/inference.py b/mmpose/apis/inference.py
--- a/mmpose/apis/inference.py
+++ b/mmpose/apis/inference.py
@@ -377,6 +377,8 @@ def vis_pose_result(model,
                         [51, 255, 51], [0, 255, 0], [0, 0, 255], [255, 0, 0],
                         [255, 255, 255]])
 
+    radius = 4
+
     if dataset == 'TopDownCocoDataset' or dataset == 'BottomUpCocoDataset' \
             or dataset == 'TopDownOCHumanDataset':
         # show the results
@@ -396,36 +398,31 @@ def vis_pose_result(model,
         skeleton = [[16, 14], [14, 12], [17, 15], [15, 13], [12, 13], [6, 12],
                     [7, 13], [6, 7], [6, 8], [7, 9], [8, 10], [9, 11], [2, 3],
                     [1, 2], [1, 3], [2, 4], [3, 5], [4, 6], [5, 7], [16, 18],
-                    [16, 19], [16, 20], [17, 21], [17, 22], [17, 23], [24, 25],
-                    [25, 26], [26, 27], [27, 28], [28, 29], [29, 30], [30, 31],
-                    [31, 32], [32, 33], [33, 34], [34, 35], [35, 36], [36, 37],
-                    [37, 38], [38, 39], [39, 40], [92, 93], [93, 94], [94, 95],
-                    [95, 96], [92, 97], [97, 98], [98, 99], [99, 100],
-                    [92, 101], [101, 102], [102, 103], [103, 104], [92, 105],
-                    [105, 106], [106, 107], [107, 108], [92, 109], [109, 110],
-                    [110, 111], [111, 112], [113, 114], [114, 115], [115, 116],
-                    [116, 117], [113, 118], [118, 119], [119, 120], [120, 121],
-                    [113, 122], [122, 123], [123, 124], [124, 125], [113, 126],
-                    [126, 127], [127, 128], [128, 129], [113, 130], [130, 131],
-                    [131, 132], [132, 133]]
+                    [16, 19], [16, 20], [17, 21], [17, 22], [17, 23], [92, 93],
+                    [93, 94], [94, 95], [95, 96], [92, 97], [97, 98], [98, 99],
+                    [99, 100], [92, 101], [101, 102], [102, 103], [103, 104],
+                    [92, 105], [105, 106], [106, 107], [107, 108], [92, 109],
+                    [109, 110], [110, 111], [111, 112], [113, 114], [114, 115],
+                    [115, 116], [116, 117], [113, 118], [118, 119], [119, 120],
+                    [120, 121], [113, 122], [122, 123], [123, 124], [124, 125],
+                    [113, 126], [126, 127], [127, 128], [128, 129], [113, 130],
+                    [130, 131], [131, 132], [132, 133]]
 
         pose_limb_color = palette[
             [0, 0, 0, 0, 7, 7, 7, 9, 9, 9, 9, 9, 16, 16, 16, 16, 16, 16, 16] +
-            [
-                16,
-            ] * 6 + [
-                19,
-            ] * 16 + [
-                19,
-            ] * 40]
+            [16, 16, 16, 16, 16, 16] + [
+                0, 0, 0, 0, 4, 4, 4, 4, 8, 8, 8, 8, 12, 12, 12, 12, 16, 16, 16,
+                16
+            ] + [
+                0, 0, 0, 0, 4, 4, 4, 4, 8, 8, 8, 8, 12, 12, 12, 12, 16, 16, 16,
+                16
+            ]]
         pose_kpt_color = palette[
-            [16, 16, 16, 16, 16, 9, 9, 9, 9, 9, 9, 0, 0, 0, 0, 0, 0] + [
-                0,
-            ] * 6 + [
-                19,
-            ] * 68 + [
+            [16, 16, 16, 16, 16, 9, 9, 9, 9, 9, 9, 0, 0, 0, 0, 0, 0] +
+            [0, 0, 0, 0, 0, 0] + [
                 19,
-            ] * 42]
+            ] * (68 + 42)]
+        radius = 1
 
     elif dataset == 'TopDownAicDataset':
         skeleton = [[3, 2], [2, 1], [1, 14], [14, 4], [4, 5], [5, 6], [9, 8],
@@ -462,6 +459,7 @@ def vis_pose_result(model,
         img,
         result,
         skeleton,
+        radius=radius,
         pose_kpt_color=pose_kpt_color,
         pose_limb_color=pose_limb_color,
         kpt_score_thr=kpt_score_thr,


Test patch: