3d visualization

main.py

@@ -1,12 +1,15 @@
 import mmpose
 import os
+import glob
 from mmpose.apis import MMPoseInferencer
-print("[INFO]: Imported modules!")
-
 import gradio as gr
 import numpy as np
 import cv2
 
+print("[INFO]: Imported modules!")
+
+
+
 # inferencer = MMPoseInferencer('hand') # 'hand', 'human , device='cuda'
 # inferencer = MMPoseInferencer('human')
 
@@ -29,38 +32,35 @@ def poses(photo):
     result_generator = inferencer(photo, 
                                   vis_out_dir =".",
                                   return_vis=True,
-                                  thickness=2)
-    
-    
-
-    # Prepare to save video
-    output_file = os.path.join("output.mp4")
+                                  thickness=2)    
 
-    fourcc = cv2.VideoWriter_fourcc(*"mp4v")  # Codec for MP4 video
-    fps = 32
-    height = 480
-    width = 640
-    size = (width,height)
+    # # Prepare to save video
+    # output_file = os.path.join("output.mp4")
 
-    out_writer = cv2.VideoWriter(output_file, fourcc, fps, size)
+    # fourcc = cv2.VideoWriter_fourcc(*"mp4v")  # Codec for MP4 video
+    # fps = 32
+    # height = 480
+    # width = 640
+    # size = (width,height)
 
-    for result in result_generator:
-        print("[INFO] Result: ", result)
-        frame = result["visualization"]
-        out_writer.write(cv2.cvtColor(frame[0], cv2.COLOR_BGR2RGB))
+    # out_writer = cv2.VideoWriter(output_file, fourcc, fps, size)
 
-    print(os.listdir())
-    print("[INFO]: Visualizing results!")
-    print(os.listdir())
-    print()
+    # for result in result_generator:
+    #     print("[INFO] Result: ", result)
+    #     frame = result["visualization"]
+    #     out_writer.write(cv2.cvtColor(frame[0], cv2.COLOR_BGR2RGB))
 
-    out_writer.release()
-    cv2.destroyAllWindows() # Closing window
+    # print(os.listdir())
+    # print("[INFO]: Visualizing results!")
+    # print(os.listdir())
+    # print()
 
+    # out_writer.release()
+    # cv2.destroyAllWindows() # Closing window
+    output_file = glob.glob("*.mp4")
 
     return output_file
 
-
 # # specify detection model by alias
 # # the available aliases include 'human', 'hand', 'face', 'animal',
 # # as well as any additional aliases defined in mmdet

requirements.txt

@@ -1,3 +1,4 @@
 gradio
 numpy
-opencv-python
+opencv-python
+glob