Spaces:
Running
on
Zero
Running
on
Zero
bugfix
Browse files
app.py
CHANGED
@@ -66,7 +66,7 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
|
|
66 |
return seed
|
67 |
|
68 |
|
69 |
-
def get_depth_map(image):
|
70 |
original_size = (image.size[1], image.size[0])
|
71 |
image = feature_extractor(images=image, return_tensors="pt").pixel_values.to("cuda")
|
72 |
with torch.no_grad(), torch.autocast("cuda"):
|
@@ -86,7 +86,7 @@ def get_depth_map(image):
|
|
86 |
return image
|
87 |
|
88 |
|
89 |
-
def upload_image_to_s3(image, account_id, access_key, secret_key, bucket_name):
|
90 |
print("upload_image_to_s3", account_id, access_key, secret_key, bucket_name)
|
91 |
connectionUrl = f"https://{account_id}.r2.cloudflarestorage.com"
|
92 |
|
@@ -110,7 +110,7 @@ def upload_image_to_s3(image, account_id, access_key, secret_key, bucket_name):
|
|
110 |
|
111 |
|
112 |
@spaces.GPU(enable_queue=True)
|
113 |
-
def process(image, image_url, prompt, n_prompt, num_steps, guidance_scale, control_strength, seed, upload_to_s3, account_id, access_key, secret_key, bucket):
|
114 |
print("process start")
|
115 |
if image_url:
|
116 |
print(image_url)
|
@@ -120,9 +120,9 @@ def process(image, image_url, prompt, n_prompt, num_steps, guidance_scale, contr
|
|
120 |
|
121 |
size = (orginal_image.size[0], orginal_image.size[1])
|
122 |
print("image size", size)
|
123 |
-
depth_image = get_depth_map(orginal_image)
|
124 |
generator = torch.Generator().manual_seed(seed)
|
125 |
-
print(prompt, n_prompt, guidance_scale, num_steps, control_strength
|
126 |
generated_image = pipe(
|
127 |
prompt=prompt,
|
128 |
negative_prompt=n_prompt,
|
@@ -136,12 +136,12 @@ def process(image, image_url, prompt, n_prompt, num_steps, guidance_scale, contr
|
|
136 |
).images[0]
|
137 |
|
138 |
if upload_to_s3:
|
139 |
-
url = upload_image_to_s3(generated_image, account_id, access_key, secret_key, bucket)
|
140 |
result = {"status": "success", "url": url}
|
141 |
else:
|
142 |
result = {"status": "success", "message": "Image generated but not uploaded"}
|
143 |
|
144 |
-
return [
|
145 |
|
146 |
with gr.Blocks() as demo:
|
147 |
|
|
|
66 |
return seed
|
67 |
|
68 |
|
69 |
+
def get_depth_map(image, progress):
|
70 |
original_size = (image.size[1], image.size[0])
|
71 |
image = feature_extractor(images=image, return_tensors="pt").pixel_values.to("cuda")
|
72 |
with torch.no_grad(), torch.autocast("cuda"):
|
|
|
86 |
return image
|
87 |
|
88 |
|
89 |
+
def upload_image_to_s3(image, account_id, access_key, secret_key, bucket_name, progress):
|
90 |
print("upload_image_to_s3", account_id, access_key, secret_key, bucket_name)
|
91 |
connectionUrl = f"https://{account_id}.r2.cloudflarestorage.com"
|
92 |
|
|
|
110 |
|
111 |
|
112 |
@spaces.GPU(enable_queue=True)
|
113 |
+
def process(image, image_url, prompt, n_prompt, num_steps, guidance_scale, control_strength, seed, upload_to_s3, account_id, access_key, secret_key, bucket, progress=gr.Progress(track_tqdm=True)):
|
114 |
print("process start")
|
115 |
if image_url:
|
116 |
print(image_url)
|
|
|
120 |
|
121 |
size = (orginal_image.size[0], orginal_image.size[1])
|
122 |
print("image size", size)
|
123 |
+
depth_image = get_depth_map(orginal_image, progress)
|
124 |
generator = torch.Generator().manual_seed(seed)
|
125 |
+
print(prompt, n_prompt, guidance_scale, num_steps, control_strength)
|
126 |
generated_image = pipe(
|
127 |
prompt=prompt,
|
128 |
negative_prompt=n_prompt,
|
|
|
136 |
).images[0]
|
137 |
|
138 |
if upload_to_s3:
|
139 |
+
url = upload_image_to_s3(generated_image, account_id, access_key, secret_key, bucket, progress)
|
140 |
result = {"status": "success", "url": url}
|
141 |
else:
|
142 |
result = {"status": "success", "message": "Image generated but not uploaded"}
|
143 |
|
144 |
+
return [orginal_image, generated_image], json.dumps(result)
|
145 |
|
146 |
with gr.Blocks() as demo:
|
147 |
|