file display

main.py

@@ -5,6 +5,7 @@ from mmpose.apis import MMPoseInferencer
 import gradio as gr
 import numpy as np
 import cv2
+import uuid
 
 print("[INFO]: Imported modules!")
 human = MMPoseInferencer("human")
@@ -31,54 +32,24 @@ print("[INFO]: Downloaded models!")
 
 def poses(photo, check):
     # Selecting the specific inferencer
-    print(check)
+
     inferencer = inferencers[check[0]] # 'hand', 'human , device='cuda'
 
     print("[INFO]: Running inference!")
-    #vis_out_dir
+    # Create out directory
+    vis_out_dir = str(uuid.uuid4())
+
     result_generator = inferencer(photo, 
-                                  vis_out_dir =".",
+                                  vis_out_dir = vis_out_dir,
                                   return_vis=True,
                                   thickness=2,
                                   rebase_keypoint_height=True)    
     
-    result = [result for result in result_generator] #next(result_generator)
-    print(type(result))
+    result = [result for result in result_generator] #next(result_generator)    
 
-    # print(["[INFO] Result from iterator: ", result])
-
-    # for r in result_generator:
-    #     print("[INFO] Single result: ", r)
-    
-    # print(type(r))
-    # # Prepare to save video
-    # output_file = os.path.join("output.mp4")
-
-    # fourcc = cv2.VideoWriter_fourcc(*"mp4v")  # Codec for MP4 video
-    # fps = 32
-    # height = 480
-    # width = 640
-    # size = (width,height)
-
-    # out_writer = cv2.VideoWriter(output_file, fourcc, fps, size)
-
-    # for result in result_generator:
-    #     print("[INFO] Result: ", result)
-    #     frame = result["visualization"]
-    #     out_writer.write(cv2.cvtColor(frame[0], cv2.COLOR_BGR2RGB))
-
-    # print(os.listdir())
-    # print("[INFO]: Visualizing results!")
-    # print(os.listdir())
-    # print()
-
-    # out_writer.release()
-    # cv2.destroyAllWindows() # Closing window
-    output_files = glob.glob(os.path.join(".", "*.mp4"))
-    print(output_files)
+    output_files = glob.glob(os.path.join(vis_out_dir, "*.mp4"))
     # 00000.mp4
     # 000000.mp4
-    print(os.listdir())
 
     return output_files[0]
 
@@ -103,7 +74,7 @@ def run():
 
     webcam = gr.Interface(
         fn=poses,
-        inputs= [gr.Video(source="webcam"), check_web],
+        inputs= [gr.Video(source="webcam", height=412), check_web],
         outputs = gr.PlayableVideo(),  #file_types=['.mp4'] #gr.Video(),
         title = 'Pose estimation', 
         description = 'Pose estimation on video',
@@ -112,7 +83,7 @@ def run():
 
     file = gr.Interface(
         poses,
-        inputs = [gr.Video(source="upload"), check_file],
+        inputs = [gr.Video(source="upload", height=412), check_file],
         outputs = gr.PlayableVideo(),
         allow_flagging=False
     )