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3da6cfd
1
Parent(s):
62c2b0b
Update app.py
Browse files
app.py
CHANGED
@@ -12,6 +12,8 @@ import os
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import spaces
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import random
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import torch
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from transformers import GLPNFeatureExtractor, GLPNForDepthEstimation
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from transformers import AutoFeatureExtractor, AutoModelForDepthEstimation
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@@ -51,6 +53,8 @@ if os.path.exists(counter_file_path):
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else:
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counter = 0
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def check_use_custom_or_no(value):
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if value is True:
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@@ -236,6 +240,19 @@ def infer(use_custom_model, model_name, weight_name, custom_lora_weight, image_i
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images[0].save(f"viteGradio/images/result{counter}.png")
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print("HELP")
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predict(images[0], counter)
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counter+=1
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with open(counter_file_path, "w") as file:
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file.write(str(counter))
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import spaces
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import random
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import torch
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import json
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from transformers import GLPNFeatureExtractor, GLPNForDepthEstimation
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from transformers import AutoFeatureExtractor, AutoModelForDepthEstimation
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else:
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counter = 0
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generated_files = []
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def check_use_custom_or_no(value):
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if value is True:
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images[0].save(f"viteGradio/images/result{counter}.png")
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print("HELP")
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predict(images[0], counter)
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with open('viteGradio/images/names.json', 'r') as f:
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filenames = json.load(f)
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result_filename = f"result{counter}.png"
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depth_filename = f"depth{counter}.png"
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filenames.append(result_filename)
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filenames.append(depth_filename)
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with open('viteGradio/images/names.json', 'w') as f:
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json.dump(filenames, f)
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counter+=1
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with open(counter_file_path, "w") as file:
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file.write(str(counter))
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