Update README.md

README.md

@@ -1,23 +1,31 @@
----
-license: unknown
-datasets:
-- fka/awesome-chatgpt-prompts
-- wikimedia/wikipedia
-- HuggingFaceH4/no_robots
-- vivym/midjourney-messages
-- berkeley-nest/Nectar
-- Lin-Chen/ShareGPT4V
-- nvidia/HelpSteer
-- Open-Orca/SlimOrca
-- gaia-benchmark/GAIA
-- MMMU/MMMU
-language:
-- ar
-- en
-metrics:
-- accuracy
-library_name: open_clip
-tags:
-- code
-- finance
----
+from transformers import DPTImageProcessor, DPTForDepthEstimation
+import torch
+import numpy as np
+from PIL import Image
+import requests
+
+url = "http://images.cocodataset.org/val2017/000000039769.jpg"
+image = Image.open(requests.get(url, stream=True).raw)
+
+processor = DPTImageProcessor.from_pretrained("Intel/dpt-large")
+model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
+
+# prepare image for the model
+inputs = processor(images=image, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model(**inputs)
+    predicted_depth = outputs.predicted_depth
+
+# interpolate to original size
+prediction = torch.nn.functional.interpolate(
+    predicted_depth.unsqueeze(1),
+    size=image.size[::-1],
+    mode="bicubic",
+    align_corners=False,
+)
+
+# visualize the prediction
+output = prediction.squeeze().cpu().numpy()
+formatted = (output * 255 / np.max(output)).astype("uint8")
+depth = Image.fromarray(formatted)