Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -39,6 +39,7 @@ import torch
|
|
39 |
# f1_metric.set(f1)
|
40 |
|
41 |
feature_extractor = ViTImageProcessor.from_pretrained("model")
|
|
|
42 |
cap_model = VisionEncoderDecoderModel.from_pretrained("model")
|
43 |
tokenizer = AutoTokenizer.from_pretrained("model")
|
44 |
|
@@ -61,7 +62,7 @@ def generate_caption(processor, model, image, tokenizer=None):
|
|
61 |
# return preds
|
62 |
inputs = processor(images=image, return_tensors="pt").to(device)
|
63 |
|
64 |
-
generated_ids = model.generate(pixel_values=inputs.pixel_values
|
65 |
|
66 |
if tokenizer is not None:
|
67 |
generated_caption = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
|
|
|
39 |
# f1_metric.set(f1)
|
40 |
|
41 |
feature_extractor = ViTImageProcessor.from_pretrained("model")
|
42 |
+
print(feature_extractor)
|
43 |
cap_model = VisionEncoderDecoderModel.from_pretrained("model")
|
44 |
tokenizer = AutoTokenizer.from_pretrained("model")
|
45 |
|
|
|
62 |
# return preds
|
63 |
inputs = processor(images=image, return_tensors="pt").to(device)
|
64 |
|
65 |
+
generated_ids = model.generate(pixel_values=inputs.pixel_values)
|
66 |
|
67 |
if tokenizer is not None:
|
68 |
generated_caption = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
|