first commit - init

app.py

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+import easyocr
+import json
+import gradio as gr
+
+# Initialize reader for your language (assuming English and French are relevant)
+reader = easyocr.Reader(['en', 'fr'])
+
+
+def extract_inbody_data(image):
+    # Extract text from the image
+    result = reader.readtext(image, detail = 0)
+
+    # Process the extracted text into structured format
+    try:
+        #print(result)
+        processed_output = extract_and_convert(result)
+        # Convert to JSON
+        json_output = json.dumps(processed_output, indent = 2)
+        return json_output
+    except (IndexError, ValueError) as e:
+        return f"Error processing image: {str(e)}"
+
+
+# Function to extract numbers and convert to float
+def extract_and_convert(data):
+    # Extract elements that represent valid numbers (using isdigit or casting as float)
+    numbers = []
+    for item in data:
+        try:
+            # Convert to float if possible
+            num = float(item)
+            numbers.append(num)
+        except ValueError:
+            continue  # Ignore non-numeric values
+
+    # Ensure we have exactly 6 values (height, age, weight, MMS, body fats, and ratio)
+    if len(numbers) >= 6:
+        height = numbers[0]
+        age = numbers[1]
+        weight = correct_float(numbers[2])
+        mms = correct_float(numbers[3])
+        body_fats = correct_float(numbers[4])
+        ratio = numbers[5]
+
+        return {
+            "Height": height,
+            "Age": age,
+            "Weight": weight,
+            "MMS": mms,
+            "Body Fats": body_fats,
+            "Ratio": ratio
+        }
+    else:
+        return {}
+
+def correct_float(num):
+    if num > 100:
+        return round(num/10,2)
+    else:
+        return num
+
+# Create Gradio Interface
+interface = gr.Interface(
+    fn = extract_inbody_data,
+    inputs = gr.Image(type = "filepath", label = "Upload InBody Image"),
+    outputs = "json",
+    title = "InBody Data Extractor",
+    description = "Upload an InBody machine screen image and extract health data (Taille, Age, Poids, MMS, TGC).",
+)
+
+if __name__ == '__main__':
+    interface.launch()

requirements.txt

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+aiofiles==23.2.1
+annotated-types==0.7.0
+anyio==4.6.0
+certifi==2024.8.30
+charset-normalizer==3.3.2
+click==8.1.7
+contourpy==1.3.0
+cycler==0.12.1
+easyocr==1.7.2
+exceptiongroup==1.2.2
+fastapi==0.115.0
+ffmpy==0.4.0
+filelock==3.16.1
+fonttools==4.54.1
+fsspec==2024.9.0
+gradio==4.44.0
+gradio_client==1.3.0
+h11==0.14.0
+httpcore==1.0.5
+httpx==0.27.2
+huggingface-hub==0.25.1
+idna==3.10
+imageio==2.35.1
+importlib_resources==6.4.5
+Jinja2==3.1.4
+kiwisolver==1.4.7
+lazy_loader==0.4
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib==3.9.2
+mdurl==0.1.2
+mpmath==1.3.0
+networkx==3.2.1
+ninja==1.11.1.1
+numpy==2.0.2
+opencv-python-headless==4.10.0.84
+orjson==3.10.7
+packaging==24.1
+pandas==2.2.3
+pillow==10.4.0
+pyclipper==1.3.0.post5
+pydantic==2.9.2
+pydantic_core==2.23.4
+pydub==0.25.1
+Pygments==2.18.0
+pyparsing==3.1.4
+python-bidi==0.6.0
+python-dateutil==2.9.0.post0
+python-multipart==0.0.10
+pytz==2024.2
+PyYAML==6.0.2
+requests==2.32.3
+rich==13.8.1
+ruff==0.6.8
+scikit-image==0.24.0
+scipy==1.13.1
+semantic-version==2.10.0
+shapely==2.0.6
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.1
+starlette==0.38.6
+sympy==1.13.3
+tifffile==2024.8.30
+tomlkit==0.12.0
+torch==2.4.1
+torchvision==0.19.1
+tqdm==4.66.5
+typer==0.12.5
+typing_extensions==4.12.2
+tzdata==2024.2
+urllib3==2.2.3
+uvicorn==0.30.6
+websockets==12.0
+zipp==3.20.2