Jyothirmai
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -6,23 +6,32 @@ import skimage.io as io
|
|
6 |
import PIL.Image
|
7 |
import difflib
|
8 |
import ViTCoAtt
|
|
|
9 |
from build_vocab import Vocabulary
|
10 |
|
11 |
|
|
|
12 |
|
13 |
# Caption generation functions
|
14 |
def generate_caption_clipgpt(image, max_tokens, temperature):
|
15 |
-
|
16 |
-
|
17 |
|
18 |
def generate_caption_vitgpt(image, max_tokens, temperature):
|
19 |
-
|
20 |
-
|
21 |
|
22 |
def generate_caption_vitCoAtt(image):
|
23 |
-
|
24 |
-
|
25 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
26 |
|
27 |
|
28 |
with gr.Row():
|
@@ -49,6 +58,9 @@ def predict(img, model_name, max_tokens, temperature):
|
|
49 |
return generate_caption_vitgpt(img, max_tokens, temperature)
|
50 |
elif model_name == "ViT-CoAttention":
|
51 |
return generate_caption_vitCoAtt(img)
|
|
|
|
|
|
|
52 |
else:
|
53 |
return "Caption generation for this model is not yet implemented."
|
54 |
|
|
|
6 |
import PIL.Image
|
7 |
import difflib
|
8 |
import ViTCoAtt
|
9 |
+
import cnn-rnn
|
10 |
from build_vocab import Vocabulary
|
11 |
|
12 |
|
13 |
+
|
14 |
|
15 |
# Caption generation functions
|
16 |
def generate_caption_clipgpt(image, max_tokens, temperature):
|
17 |
+
caption = clipGPT.generate_caption_clipgpt(image, max_tokens, temperature)
|
18 |
+
return caption
|
19 |
|
20 |
def generate_caption_vitgpt(image, max_tokens, temperature):
|
21 |
+
caption = vitGPT.generate_caption(image, max_tokens, temperature)
|
22 |
+
return caption
|
23 |
|
24 |
def generate_caption_vitCoAtt(image):
|
25 |
+
caption = ViTCoAtt.CaptionSampler.main(image)
|
26 |
+
return caption
|
27 |
|
28 |
+
def generate_caption_cnnrnn(image):
|
29 |
+
# with open('/content/Image_features_ecoder_decoder.pickle', 'rb') as f:
|
30 |
+
# Xnet_features = pickle.load(f)
|
31 |
+
# image = Xnet_features[image]
|
32 |
+
# caption = cnn-rnn.get_result(image)
|
33 |
+
caption = ""
|
34 |
+
return caption
|
35 |
|
36 |
|
37 |
with gr.Row():
|
|
|
58 |
return generate_caption_vitgpt(img, max_tokens, temperature)
|
59 |
elif model_name == "ViT-CoAttention":
|
60 |
return generate_caption_vitCoAtt(img)
|
61 |
+
elif model_name == "Baseline Model CNN-RNN":
|
62 |
+
print(img)
|
63 |
+
return generate_caption_cnnrnn(img)
|
64 |
else:
|
65 |
return "Caption generation for this model is not yet implemented."
|
66 |
|