application

app.py

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+from fastapi import FastAPI, File, UploadFile
+# from depth_est_deprecated import DepthEstimation
+from depth_est import DepthEstimation
+import base64
+
+app = FastAPI()
+
+# @app.get("/depth")
+# async def depth(image: str):
+    
+#     depth_base64 = DepthEstimation(image).run_depth()
+#     return {"output": depth_base64}
+
+
+# @app.get("/depth")
+# async def depth(file: UploadFile):
+    
+#     depth_base64 = DepthEstimation(File).run_depth()
+#     return {"output": depth_base64}
+
+@app.post("/depth")
+async def depth(file: UploadFile):
+    file_data = await file.read()
+    encoded_file_data = base64.b64encode(file_data).decode('utf-8')
+    depth_base64 = DepthEstimation(encoded_file_data).run_depth()
+    return {"file_data": depth_base64}
+

depth_est.py

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+from PIL import Image
+import cv2
+from transformers import pipeline
+import base64
+import requests
+import io
+import numpy as np
+
+def convert_img_base64(img):
+    with open(img, 'rb') as file:
+        base64_image = base64.b64encode(file.read())
+    return base64_image
+
+
+
+class DepthEstimation():
+    def __init__(self, img_base64):
+        self.img_base64 = img_base64
+
+    def convert_from_base64(self):
+        image_data = base64.b64decode(self.img_base64)
+        image = Image.open(io.BytesIO(image_data))
+        return image
+
+    def run_depth(self):
+        image_data = self.convert_from_base64()
+        
+        pipe = pipeline("depth-estimation", model="Intel/dpt-hybrid-midas")
+        depth = pipe(image_data)
+        depth_map = depth['predicted_depth']
+        
+        # Convert the tensor to a NumPy array and normalize
+        depth_map = depth_map.squeeze().cpu().numpy()  # Remove batch dimension
+        depth_map = np.uint8(depth_map / depth_map.max() * 255)  # Normalize to 0-255
+        
+        # Convert depth map to PIL Image
+        depth_image = Image.fromarray(depth_map)
+        
+        # Save the depth image to a bytes buffer
+        buffer = io.BytesIO()
+        depth_image.save(buffer, format='PNG')
+        image_bytes = buffer.getvalue()
+        
+        # Encode the bytes to base64
+        base64_string = base64.b64encode(image_bytes).decode()
+        
+        # Decode and display for verification
+        image_data = base64.b64decode(base64_string)
+        image = Image.open(io.BytesIO(image_data))
+        image.show()
+        image.save('output_image.png')
+
+        return base64_string
+
+
+if __name__ == "__main__":
+    img_path = 'img3.jpg'
+    base64_image = convert_img_base64(img_path)
+    DepthEstimation(base64_image).run_depth()

requirements.txt

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+fastapi
+requests
+numpy
+transformers
+uvicorn
+python-multipart
+pillow
+opencv-python