Initial commit: Add Gradio app and model

.gitattributes

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+*.pth filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+title: Plant Species Classification
+emoji: 🌿
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 4.28.3
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# 🌿 Plant Species Classification
+
+This is a Gradio app for the AML Group Project by PsychicFireSong.
+
+It uses a `ConvNextV2` model fine-tuned on the Herbarium Field dataset to classify plant species from images.
+
+**Models Available:**
+- **Herbarium Species Classifier:** The primary model for classification.
+- **Future Model 1 (Placeholder):** Not yet implemented.
+- **Future Model 2 (Placeholder):** Not yet implemented.

app.py

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+import gradio as gr
+import torch
+import pandas as pd
+import os
+from torchvision import transforms
+from PIL import Image
+from transformers import ConvNextV2ForImageClassification
+
+# --- Configuration ---
+# Paths are relative to the app's root directory in the Hugging Face Space
+DATA_DIR = '.'
+LIST_DIR = os.path.join(DATA_DIR, 'list')
+MODEL_PATH_HERBARIUM = os.path.join(DATA_DIR, 'herbarium_convnext_v2_base.pth')
+SPECIES_LIST_TXT = os.path.join(LIST_DIR, 'species_list.txt')
+
+DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
+# --- Load Species Information ---
+try:
+    species_df = pd.read_csv(SPECIES_LIST_TXT, sep=';', header=None, names=['class_id', 'species_name'])
+    class_names = list(species_df['species_name'])
+    num_labels = len(class_names)
+except FileNotFoundError:
+    # Fallback if the species list is not found
+    class_names = [f"Class {i}" for i in range(100)] # Assuming 100 classes as a fallback
+    num_labels = 100
+    print(f"Warning: '{SPECIES_LIST_TXT}' not found. Using generic class names.")
+
+
+# --- Image Transformations ---
+data_transforms = transforms.Compose([
+    transforms.Resize(256),
+    transforms.CenterCrop(224),
+    transforms.ToTensor(),
+    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+])
+
+# --- Model Loading ---
+def load_herbarium_model():
+    """Loads the Herbarium ConvNextV2 model."""
+    model = ConvNextV2ForImageClassification.from_pretrained(
+        "facebook/convnextv2-base-22k-224",
+        num_labels=num_labels,
+        ignore_mismatched_sizes=True
+    )
+    try:
+        # Load the state dictionary
+        model.load_state_dict(torch.load(MODEL_PATH_HERBARIUM, map_location=DEVICE))
+    except FileNotFoundError:
+        print(f"Warning: Model weights not found at '{MODEL_PATH_HERBARIUM}'. The model is using pre-trained weights, not fine-tuned ones.")
+    except Exception as e:
+        print(f"Error loading model weights: {e}. The model is using pre-trained weights.")
+        
+    model = model.to(DEVICE)
+    model.eval()
+    return model
+
+# Load the primary model
+herbarium_model = load_herbarium_model()
+
+# --- Prediction Functions ---
+def predict_herbarium(image):
+    """Runs inference on the herbarium model."""
+    if image is None:
+        return "Please upload an image."
+        
+    # Preprocess the image
+    image = data_transforms(image).unsqueeze(0)
+    image = image.to(DEVICE)
+
+    # Get model predictions
+    with torch.no_grad():
+        outputs = herbarium_model(image).logits
+        probabilities = torch.nn.functional.softmax(outputs, dim=1)[0]
+        
+        # Get top 5 predictions
+        top5_prob, top5_indices = torch.topk(probabilities, 5)
+        
+    # Format results
+    results = {class_names[i]: f"{p:.3f}" for i, p in zip(top5_indices, top5_prob)}
+    return results
+
+def predict_placeholder_1(image):
+    """Placeholder function for the second model."""
+    if image is None:
+        return "Please upload an image."
+    return "Model 2 is not available yet. Please check back later."
+
+def predict_placeholder_2(image):
+    """Placeholder function for the third model."""
+    if image is None:
+        return "Please upload an image."
+    return "Model 3 is not available yet. Please check back later."
+
+# --- Main Prediction Logic ---
+def predict(model_choice, image):
+    """Routes the prediction to the chosen model."""
+    if model_choice == "Herbarium Species Classifier":
+        return predict_herbarium(image)
+    elif model_choice == "Future Model 1 (Placeholder)":
+        return predict_placeholder_1(image)
+    elif model_choice == "Future Model 2 (Placeholder)":
+        return predict_placeholder_2(image)
+    else:
+        return "Invalid model selected."
+
+# --- Gradio Interface ---
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # 🌿 Plant Species Classification
+        ## AML Group Project - PsychicFireSong
+        Upload an image of a plant to classify it. Select a model from the dropdown below.
+        """
+    )
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            model_selector = gr.Dropdown(
+                label="Select Model",
+                choices=[
+                    "Herbarium Species Classifier", 
+                    "Future Model 1 (Placeholder)", 
+                    "Future Model 2 (Placeholder)"
+                ],
+                value="Herbarium Species Classifier"
+            )
+            image_input = gr.Image(type="pil", label="Upload Plant Image")
+            submit_button = gr.Button("Classify", variant="primary")
+
+        with gr.Column(scale=1):
+            output_label = gr.Label(label="Top 5 Predictions", num_top_classes=5)
+
+    submit_button.click(
+        fn=predict,
+        inputs=[model_selector, image_input],
+        outputs=output_label
+    )
+    
+    gr.Examples(
+        examples=[
+            # Add paths to example images if you have any in your project
+            # e.g., os.path.join("examples", "example1.jpg")
+        ],
+        inputs=image_input,
+        outputs=output_label,
+        fn=lambda img: predict("Herbarium Species Classifier", img),
+        cache_examples=False
+    )
+
+if __name__ == "__main__":
+    demo.launch()

herbarium_convnext_v2_base.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:837cca126e235c0ae822770470e38a3621b81b0ba7e915aaef2b15a7f66914e6
+size 351335085

list/species_list.txt

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+105951; Maripa glabra Choisy
+106023; Merremia umbellata (L.) Hallier f.
+106387; Costus arabicus L.
+106461; Costus scaber Ruiz Pav.
+106466; Costus spiralis (Jacq.) Roscoe
+110432; Evodianthus funifer (Poit.) Lindm.
+116853; Pteridium arachnoideum (Kaulf.) Maxon
+119986; Olfersia cervina (L.) Kunze
+120497; Diospyros capreifolia Mart. ex Hiern
+121836; Sloanea grandiflora Sm.
+121841; Sloanea guianensis (Aubl.) Benth.
+12254; Anacardium occidentale L.
+12518; Mangifera indica L.
+125412; Sphyrospermum cordifolium Benth.
+126895; Syngonanthus caulescens (Poir.) Ruhland
+127007; Tonina fluviatilis Aubl.
+127097; Erythroxylum fimbriatum Peyr.
+127151; Erythroxylum macrophyllum Cav.
+127242; Erythroxylum squamatum Sw.
+12910; Spondias mombin L.
+12922; Tapirira guianensis Aubl.
+129645; Croton schiedeanus Schltdl.
+130657; Euphorbia cotinifolia L.
+131079; Euphorbia heterophylla L.
+131736; Euphorbia prostrata Aiton
+132107; Euphorbia thymifolia L.
+132113; Euphorbia tithymaloides L.
+132431; Hura crepitans L.
+132476; Jatropha curcas L.
+132501; Jatropha gossypiifolia L.
+13276; Annona ambotay Aubl.
+13325; Annona foetida Mart.
+13330; Annona glabra L.
+133595; Ricinus communis L.
+133617; Sapium glandulosum (L.) Morong
+13370; Annona muricata L.
+136761; Potalia amara Aubl.
+138662; Chrysothemis pulchella (Donn ex Sims) Decne.
+140367; Lembocarpus amoenus Leeuwenb.
+141068; Sinningia incarnata (Aubl.) D.L.Denham
+141332; Dicranopteris flexuosa (Schrad.) Underw.
+141336; Dicranopteris pectinata (Willd.) Underw.
+142550; Heliconia chartacea Lane ex Barreiros
+142736; Hernandia guianensis Aubl.
+143496; Hymenophyllum hirsutum (L.) Sw.
+14353; Guatteria ouregou (Aubl.) Dunal
+143706; Trichomanes diversifrons (Bory) Mett. ex Sadeb.
+143758; Trichomanes punctatum Poir.
+14401; Guatteria scandens Ducke
+144394; Didymochlaena truncatula (Sw.) J. Sm.
+145020; Cipura paludosa Aubl.
+148220; Aegiphila macrantha Ducke
+148977; Clerodendrum paniculatum L.
+149264; Congea tomentosa Roxb.
+149682; Gmelina philippensis Cham.
+149919; Holmskioldia sanguinea Retz.
+150135; Hyptis lanceolata Poir.
+15014; Rollinia mucosa (Jacq.) Baill.
+151469; Ocimum campechianum Mill.
+151593; Orthosiphon aristatus (Blume) Miq.
+15318; Xylopia aromatica (Lam.) Mart.
+15330; Xylopia cayennensis Maas
+15355; Xylopia frutescens Aubl.
+156516; Aniba guianensis Aubl.
+156526; Aniba megaphylla Mez
+158341; Nectandra cissiflora Nees
+158592; Ocotea cernua (Nees) Mez
+158653; Ocotea floribunda (Sw.) Mez
+158736; Ocotea longifolia Kunth
+158793; Ocotea oblonga (Meisn.) Mez
+158833; Ocotea puberula (Rich.) Nees
+159434; Couratari guianensis Aubl.
+159516; Eschweilera parviflora (Aubl.) Miers
+159518; Eschweilera pedicellata (Rich.) S.A.Mori
+160570; Acacia mangium Willd.
+166822; Caesalpinia pulcherrima (L.) Sw.
+166869; Cajanus cajan (L.) Millsp.
+169293; Crotalaria retusa L.
+171727; Erythrina fusca Lour.
+173914; Inga alba (Sw.) Willd.
+173972; Inga capitata Desv.
+174017; Inga edulis Mart.
+177730; Mimosa pigra L.
+177775; Mimosa pudica L.
+189669; Punica granatum L.
+191642; Adansonia digitata L.
+19165; Allamanda cathartica L.
+192311; Ceiba pentandra (L.) Gaertn.
+194035; Hibiscus rosa-sinensis L.
+19489; Asclepias curassavica L.
+209328; Psidium guineense Sw.
+211059; Nephrolepis biserrata (Sw.) Schott
+244705; Averrhoa carambola L.
+248392; Turnera ulmifolia L.
+254180; Piper peltatum L.
+275029; Eichhornia crassipes (Mart.) Solms
+280085; Ceratopteris thalictroides (L.) Brongn.
+280698; Pityrogramma calomelanos (L.) Link
+285398; Cassipourea guianensis Aubl.
+29686; Oreopanax capitatus (Jacq.) Decne. Planch.

requirements.txt

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+torch
+torchvision
+transformers
+pandas
+gradio