AleNunezArroyo commited on
Commit
7a357fb
·
1 Parent(s): 236733d
Files changed (3) hide show
  1. app.py +10 -13
  2. requirements.txt +1 -3
  3. utils/upload.py +0 -24
app.py CHANGED
@@ -1,6 +1,5 @@
1
  import gradio as gr
2
  from utils.loading import load_model
3
- from utils.upload import upload_firebase
4
 
5
  TITLE = 'Pose Detection App 🕺🤸‍♀️'
6
  DESCRIPTION = '''
@@ -42,7 +41,6 @@ def process_image(input_img, pos, confidence):
42
  Returns:
43
  np.ndarray: Imagen anotada con los resultados de la detección.
44
  """
45
- upload_firebase(input_img)
46
  img = load_model(input_img, float(pos), int(confidence))
47
  return img
48
 
@@ -51,16 +49,15 @@ pos_slider = gr.Slider(minimum=MIN_CONF, maximum=MAX_CONF, value=0.5, step=0.1,
51
  confidence_slider = gr.Slider(minimum=MIN_POS, maximum=MAX_POS, value=3, step=1, label="Número de Poses", interactive=True)
52
 
53
  # Creación de la interfaz de Gradio
54
- demo = gr.Interface(fn=process_image,
55
- inputs=[gr.Image(), pos_slider, confidence_slider],
56
- outputs=gr.Image(),
57
- title=TITLE,
58
- description=DESCRIPTION,
59
- allow_flagging="never",
60
- examples=
61
- [
62
- ['examples/pexels-august-de-richelieu-4427430.jpg', 0.5, 5],
63
- ['examples/pexels-danxavier-1121796.jpg', 0.9, 1],
64
- ])
65
 
66
  demo.queue().launch()
 
1
  import gradio as gr
2
  from utils.loading import load_model
 
3
 
4
  TITLE = 'Pose Detection App 🕺🤸‍♀️'
5
  DESCRIPTION = '''
 
41
  Returns:
42
  np.ndarray: Imagen anotada con los resultados de la detección.
43
  """
 
44
  img = load_model(input_img, float(pos), int(confidence))
45
  return img
46
 
 
49
  confidence_slider = gr.Slider(minimum=MIN_POS, maximum=MAX_POS, value=3, step=1, label="Número de Poses", interactive=True)
50
 
51
  # Creación de la interfaz de Gradio
52
+ demo = gr.Interface(
53
+ fn=process_image,
54
+ inputs=[gr.Image(), pos_slider, confidence_slider],
55
+ outputs=gr.Image(),
56
+ title=TITLE,
57
+ description=DESCRIPTION,
58
+ allow_flagging="never",
59
+ examples=[
60
+ ['examples/pexels-august-de-richelieu-4427430.jpg', 0.5, 5],
61
+ ['examples/pexels-danxavier-1121796.jpg', 0.9, 1],])
 
62
 
63
  demo.queue().launch()
requirements.txt CHANGED
@@ -1,5 +1,3 @@
1
  gradio==4.38.1
2
  mediapipe==0.10.14
3
- numpy==1.26.3
4
- opencv-python==4.9.0.80
5
- firebase-admin==6.5.0
 
1
  gradio==4.38.1
2
  mediapipe==0.10.14
3
+ numpy==1.26.3
 
 
utils/upload.py DELETED
@@ -1,24 +0,0 @@
1
- import firebase_admin
2
- from firebase_admin import credentials, storage
3
- import random
4
- from datetime import datetime
5
- import cv2
6
-
7
- if not firebase_admin._apps:
8
- cred = credentials.Certificate('utils/credential.json')
9
- firebase_admin.initialize_app(cred, {'storageBucket':'load-images-5b386.appspot.com'})
10
- bucket = storage.bucket()
11
-
12
- def upload_firebase(img):
13
- imagen_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
14
-
15
- # Convertir la imagen a un objeto de bytes
16
- _, buffer = cv2.imencode('.png', imagen_rgb)
17
- image_bytes = buffer.tobytes()
18
- # Subir la imagen directamente a Firebase Storage
19
- bucket = storage.bucket()
20
-
21
- date = datetime.now().strftime('%Y-%m-%d_%H:%M:%S')
22
- id = str(random.randint(1, 100000000))
23
- blob = bucket.blob(f'images/{date}_{id}.png')
24
- blob.upload_from_string(image_bytes, content_type='image/png')