Upload folder using huggingface_hub

Dockerfile

@@ -0,0 +1,32 @@
+FROM tensorflow/tensorflow:2.15.0-gpu
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements and install Python dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY app.py .
+
+# Copy model files (you'll need to add these)
+COPY model18cls/ ./model18cls/
+
+# Create non-root user for HF Spaces
+RUN useradd -m -u 1000 user
+USER user
+
+# Set environment variables
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH \
+    PYTHONUNBUFFERED=1
+
+EXPOSE 7860
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,11 +1,33 @@
 ---
-title: Shia Brain
-emoji: 🏆
-colorFrom: purple
+title: SHIA - Brain MRI Segmentation
+emoji: 🧠
+colorFrom: blue
 colorTo: purple
 sdk: docker
+app_port: 7860
 pinned: false
 license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# SHIA - Structured Health Intelligence for Alzheimer's
+
+Fast GPU-accelerated brain MRI segmentation API.
+
+## API Endpoints
+
+### POST /segment
+Upload a NIfTI file (.nii or .nii.gz) for segmentation.
+
+```bash
+curl -X POST -F "file=@brain.nii.gz" https://YOUR-SPACE.hf.space/segment
+```
+
+### POST /segment/compact
+Same as above but returns base64-gzipped results (more efficient for large volumes).
+
+### GET /health
+Check API status and GPU availability.
+
+## Credits
+
+Based on [BrainChop](https://github.com/neuroneural/brainchop) by the Neuroneural Lab.

app.py

@@ -0,0 +1,235 @@
+import os
+import io
+import time
+import json
+import numpy as np
+import tensorflow as tf
+import nibabel as nib
+from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+import gzip
+
+app = FastAPI(title="SHIA - Brain MRI Segmentation API")
+
+# Enable CORS for frontend
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Global model cache
+model = None
+MODEL_PATH = "model18cls"
+
+def load_tfjs_model(model_path):
+    """
+    Load a TensorFlow.js LayersModel from model.json + weight shards.
+    Converts it to a Keras model for inference.
+    """
+    import tensorflowjs as tfjs
+
+    # Load the tfjs model and convert to Keras
+    model = tfjs.converters.load_keras_model(os.path.join(model_path, "model.json"))
+    return model
+
+def load_model():
+    """Load TensorFlow model on startup"""
+    global model
+    if model is None:
+        print(f"Loading model from {MODEL_PATH}...")
+
+        # Check if it's a tfjs model (has model.json) or SavedModel
+        model_json_path = os.path.join(MODEL_PATH, "model.json")
+        if os.path.exists(model_json_path):
+            print("Detected TensorFlow.js format, converting...")
+            model = load_tfjs_model(MODEL_PATH)
+        else:
+            print("Loading as SavedModel format...")
+            model = tf.keras.models.load_model(MODEL_PATH)
+
+        print("Model loaded successfully!")
+        print(f"Input shape: {model.input_shape}")
+        print(f"Output shape: {model.output_shape}")
+    return model
+
+def parse_nifti(file_bytes: bytes):
+    """Parse NIfTI file from bytes"""
+    # Check if gzipped
+    if file_bytes[:2] == b'\x1f\x8b':
+        file_bytes = gzip.decompress(file_bytes)
+
+    # Use nibabel with BytesIO
+    fh = nib.FileHolder(fileobj=io.BytesIO(file_bytes))
+    img = nib.Nifti1Image.from_file_map({'header': fh, 'image': fh})
+
+    return img.get_fdata(), img.header
+
+def min_max_normalize(data):
+    """Normalize data to 0-1 range"""
+    data_min = data.min()
+    data_max = data.max()
+    if data_max - data_min == 0:
+        return data
+    return (data - data_min) / (data_max - data_min)
+
+def preprocess_volume(data):
+    """Preprocess MRI volume for model input"""
+    # Normalize
+    data = min_max_normalize(data)
+
+    # Ensure float32
+    data = data.astype(np.float32)
+
+    # Transpose if needed (depends on model training)
+    # Model expects [batch, D, H, W, channels]
+    data = np.transpose(data, (2, 1, 0))  # Adjust axes as needed
+
+    # Add batch and channel dimensions
+    data = np.expand_dims(data, axis=0)  # batch
+    data = np.expand_dims(data, axis=-1)  # channel
+
+    return data
+
+def run_inference(data):
+    """Run model inference on preprocessed data"""
+    loaded_model = load_model()
+
+    # Run prediction
+    prediction = loaded_model.predict(data, verbose=0)
+
+    # Get argmax for segmentation labels
+    segmentation = np.argmax(prediction, axis=-1)
+
+    # Remove batch dimension and transpose back
+    segmentation = segmentation[0]
+    segmentation = np.transpose(segmentation, (2, 1, 0))
+
+    return segmentation
+
+@app.on_event("startup")
+async def startup_event():
+    """Load model on startup"""
+    load_model()
+
+@app.get("/")
+async def root():
+    """Health check endpoint"""
+    return {
+        "status": "ok",
+        "service": "SHIA - Brain MRI Segmentation",
+        "model_loaded": model is not None
+    }
+
+@app.get("/health")
+async def health():
+    """Health check"""
+    return {"status": "healthy", "gpu": tf.config.list_physical_devices('GPU')}
+
+@app.post("/segment")
+async def segment(file: UploadFile = File(...)):
+    """
+    Segment a brain MRI scan.
+
+    Upload a NIfTI file (.nii or .nii.gz) and receive segmentation results.
+    """
+    try:
+        start_time = time.time()
+
+        # Validate file type
+        if not file.filename.endswith(('.nii', '.nii.gz')):
+            raise HTTPException(400, "File must be a NIfTI file (.nii or .nii.gz)")
+
+        # Read file
+        print(f"Processing: {file.filename}")
+        file_bytes = await file.read()
+
+        # Parse NIfTI
+        parse_start = time.time()
+        data, header = parse_nifti(file_bytes)
+        parse_time = time.time() - parse_start
+        print(f"Volume shape: {data.shape}, Parse time: {parse_time:.2f}s")
+
+        # Preprocess
+        preprocess_start = time.time()
+        processed = preprocess_volume(data)
+        preprocess_time = time.time() - preprocess_start
+        print(f"Preprocessed shape: {processed.shape}, Time: {preprocess_time:.2f}s")
+
+        # Run inference
+        inference_start = time.time()
+        segmentation = run_inference(processed)
+        inference_time = time.time() - inference_start
+        print(f"Inference time: {inference_time:.2f}s")
+
+        total_time = time.time() - start_time
+
+        # Get unique labels found
+        unique_labels = np.unique(segmentation).tolist()
+
+        return JSONResponse({
+            "success": True,
+            "filename": file.filename,
+            "original_shape": list(data.shape),
+            "segmentation_shape": list(segmentation.shape),
+            "unique_labels": unique_labels,
+            "num_labels": len(unique_labels),
+            "timing": {
+                "parse": round(parse_time, 3),
+                "preprocess": round(preprocess_time, 3),
+                "inference": round(inference_time, 3),
+                "total": round(total_time, 3)
+            },
+            # Return segmentation as nested list (can be large!)
+            "segmentation": segmentation.astype(np.uint8).tolist()
+        })
+
+    except Exception as e:
+        print(f"Error: {str(e)}")
+        raise HTTPException(500, f"Segmentation failed: {str(e)}")
+
+@app.post("/segment/compact")
+async def segment_compact(file: UploadFile = File(...)):
+    """
+    Segment a brain MRI scan and return compressed results.
+
+    Returns base64-encoded gzipped segmentation for efficiency.
+    """
+    import base64
+
+    try:
+        start_time = time.time()
+
+        if not file.filename.endswith(('.nii', '.nii.gz')):
+            raise HTTPException(400, "File must be a NIfTI file (.nii or .nii.gz)")
+
+        file_bytes = await file.read()
+        data, header = parse_nifti(file_bytes)
+        processed = preprocess_volume(data)
+        segmentation = run_inference(processed)
+
+        total_time = time.time() - start_time
+
+        # Compress segmentation
+        seg_bytes = segmentation.astype(np.uint8).tobytes()
+        compressed = gzip.compress(seg_bytes)
+        encoded = base64.b64encode(compressed).decode('utf-8')
+
+        return JSONResponse({
+            "success": True,
+            "shape": list(segmentation.shape),
+            "dtype": "uint8",
+            "encoding": "base64_gzip",
+            "inference_time": round(total_time, 3),
+            "data": encoded
+        })
+
+    except Exception as e:
+        raise HTTPException(500, f"Segmentation failed: {str(e)}")
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)

model18cls/colormap.json

@@ -0,0 +1,6 @@
+{
+    "R": [ 0, 245, 205, 120, 196, 220, 230, 0, 122, 236, 12, 204, 42, 119, 220, 103, 255, 165],
+    "G": [ 0, 245, 62, 18, 58, 248, 148, 118, 186, 13, 48, 182, 204, 159, 216, 255, 165, 42],
+    "B": [ 0, 245, 78, 134, 250, 164, 34, 14, 220, 176, 255, 142, 164, 176, 20, 255, 0, 42],
+    "labels": [ "Unknown", "Cerebral-White-Matter", "Cerebral-Cortex", "Lateral-Ventricle", "Inferior-Lateral-Ventricle", "Cerebellum-White-Matter", "Cerebellum-Cortex", "Thalamus", "Caudate", "Putamen", "Pallidum", "3rd-Ventricle", "4th-Ventricle", "Brain-Stem", "Hippocampus", "Amygdala", "Accumbens-area", "VentralDC"]
+}

model18cls/model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:725096439f64ece1ca45ec3c5115c9fa6004f6538cac3032b85966d3772b605e
+size 385632

model18cls/model.json

@@ -0,0 +1,808 @@
+{
+    "format": "layers-model",
+    "generatedBy": "keras v2.7.0",
+    "convertedBy": "TensorFlow.js Converter v3.9.0",
+    "modelTopology": {
+        "keras_version": "2.6.0",
+        "backend": "tensorflow",
+        "model_config": {
+            "class_name": "Functional",
+            "config": {
+                "name": "model",
+                "layers": [
+                    {
+                        "class_name": "InputLayer",
+                        "config": {
+                            "batch_input_shape": [
+                                null,
+                                256,
+                                256,
+                                256,
+                                1
+                            ],
+                            "dtype": "float32",
+                            "sparse": false,
+                            "ragged": false,
+                            "name": "input"
+                        },
+                        "name": "input",
+                        "inbound_nodes": []
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_0",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_0",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "input",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_1",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_1",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_0",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_2",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                2,
+                                2,
+                                2
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_2",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_1",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_3",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_3",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_2",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_4",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                4,
+                                4,
+                                4
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_4",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_3",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_5",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_5",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_4",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_6",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                8,
+                                8,
+                                8
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_6",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_5",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_7",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_7",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_6",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_8",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                16,
+                                16,
+                                16
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_8",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_7",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_9",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_9",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_8",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_10",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                8,
+                                8,
+                                8
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_10",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_9",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_11",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_11",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_10",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_12",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                4,
+                                4,
+                                4
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_12",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_11",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_13",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_13",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_12",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_14",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                2,
+                                2,
+                                2
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_14",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_13",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_15",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_15",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_14",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "conv3d_16",
+                            "trainable": false,
+                            "filters": 21,
+                            "kernel_size": [
+                                3,
+                                3,
+                                3
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "conv3d_16",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_15",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Activation",
+                        "config": {
+                            "name": "activation_17",
+                            "trainable": false,
+                            "dtype": "float32",
+                            "activation": "elu"
+                        },
+                        "name": "activation_17",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "conv3d_16",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    },
+                    {
+                        "class_name": "Conv3D",
+                        "config": {
+                            "name": "output",
+                            "trainable": false,
+                            "filters": 18,
+                            "kernel_size": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "strides": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "dilation_rate": [
+                                1,
+                                1,
+                                1
+                            ],
+                            "padding": "same",
+                            "data_format": "channels_last",
+                            "activation": "linear",
+                            "use_bias": true,
+                            "dtype": "float32"
+                        },
+                        "name": "output",
+                        "inbound_nodes": [
+                            [
+                                [
+                                    "activation_17",
+                                    0,
+                                    0,
+                                    {}
+                                ]
+                            ]
+                        ]
+                    }
+                ],
+                "input_layers": [
+                    [
+                        "input",
+                        0,
+                        0
+                    ]
+                ],
+                "output_layers": [
+                    [
+                        "output",
+                        0,
+                        0
+                    ]
+                ]
+            }
+        }
+    },
+    "weightsManifest": [
+        {
+            "paths": [
+                "model.bin"
+            ],
+            "weights": [
+                {
+                    "name": "conv3d_0/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        1,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_0/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_2/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_2/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_4/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_4/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_6/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_6/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_8/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_8/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_10/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_10/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_12/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_12/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_14/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_14/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_16/kernel",
+                    "shape": [
+                        3,
+                        3,
+                        3,
+                        21,
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "conv3d_16/bias",
+                    "shape": [
+                        21
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "output/kernel",
+                    "shape": [
+                        1,
+                        1,
+                        1,
+                        21,
+                        18
+                    ],
+                    "dtype": "float32"
+                },
+                {
+                    "name": "output/bias",
+                    "shape": [
+                        18
+                    ],
+                    "dtype": "float32"
+                }
+            ]
+        }
+    ]
+}

requirements.txt

@@ -0,0 +1,7 @@
+fastapi==0.104.1
+uvicorn[standard]==0.24.0
+python-multipart==0.0.6
+tensorflow==2.15.0
+tensorflowjs==4.15.0
+nibabel==5.2.0
+numpy==1.26.2

setup.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+# Setup script for Hugging Face Space
+
+# Copy model files to huggingface directory
+echo "Copying model files..."
+cp -r ../public/models/model18cls ./model18cls
+
+echo "Done! Now you can:"
+echo "1. Create a new Space on huggingface.co/new-space"
+echo "2. Select 'Docker' as the SDK"
+echo "3. Select 'GPU' hardware (T4 is free)"
+echo "4. Upload all files from this directory"
+echo ""
+echo "Or use the HF CLI:"
+echo "  huggingface-cli login"
+echo "  huggingface-cli repo create shia-brain --type space --space_sdk docker"
+echo "  cd huggingface && git init && git remote add origin https://huggingface.co/spaces/YOUR_USERNAME/shia-brain"
+echo "  git add . && git commit -m 'Initial commit' && git push"